KR100796905B1 - System for Quality Control of DataBase - Google Patents

Abstract

The present invention provides data including at least one or more standard data, model data, management data, and business data, and conceptual data model information, data reference model information, logical data model information, physical data model information, and database corresponding to the model data. A database having information and user view information, data including at least one standard data, model data, management data, and business data; conceptual data model information, data reference model information, and logical data models corresponding to the model data; At least one quality management module for managing information, physical data model information, database information, and user view information according to a predetermined data management process, and at least one terminal for managing the database quality through the quality management module. Wherein more than made, and thereby has the advantage of quality control database to manage the quality of the database by maintaining the quality of the database based on the database, quality management framework consisting of a wide, short time and low cost.

 Data, Database, Quality, Quality Management, Framework

Description

Database Quality Management System {System for Quality Control of DataBase}

1 is a diagram illustrating a database quality management framework structure according to the present invention.

2 is a diagram illustrating a configuration of a database quality management system according to an embodiment of the present invention.

3 is a diagram illustrating an overview data model according to an embodiment of the present invention.

4 is a diagram illustrating a conceptual data model according to an embodiment of the present invention.

5 is a diagram illustrating a data reference model according to an embodiment of the present invention.

6 is a diagram illustrating a logical data model according to an embodiment of the present invention.

7 is a diagram illustrating a physical data model according to an embodiment of the present invention.

8 is a diagram illustrating a table code of a database according to an embodiment of the present invention.

9A and 9B illustrate database tables according to an embodiment of the present invention.

10 illustrates a user view according to an embodiment of the present invention.

11 is a diagram illustrating a standard data management screen according to an embodiment of the present invention.

12 is a diagram illustrating a model data management screen according to an embodiment of the present invention.

13A and 13B are views illustrating management data management screens according to an embodiment of the present invention.

14A is a diagram illustrating a data quality control main process according to an embodiment of the present invention.

14B is a diagram illustrating a data management policy establishment process according to an embodiment of the present invention.

14C is a diagram illustrating a data standard definition process according to an embodiment of the present invention.

14D illustrates a data standard evaluation process in accordance with an embodiment of the present invention.

14E illustrates a data model operating process according to an embodiment of the present invention.

14F is a diagram illustrating a data flow management process according to an embodiment of the present invention.

14G illustrates a database operating process in accordance with an embodiment of the present invention.

14H is a diagram illustrating a data utilization management process according to an embodiment of the present invention.

14I illustrates a requirements management process in accordance with an embodiment of the present invention.

15A is a diagram illustrating a data quality control main process according to an embodiment of the present invention.

15B is a diagram illustrating a data management policy establishment process according to an embodiment of the present invention.

15C is a diagram illustrating a data standard change process according to an embodiment of the present invention.

15D illustrates a data standard evaluation process in accordance with an embodiment of the present invention.

15E illustrates a data model improvement process according to an embodiment of the present invention.

15F is a diagram illustrating a data flow improvement process according to an embodiment of the present invention.

15G is a diagram illustrating a database improvement process according to an embodiment of the present invention.

15H is a diagram illustrating a data utilization management process according to an embodiment of the present invention.

15I illustrates a requirements management process in accordance with an embodiment of the present invention.

16A is a diagram illustrating a data quality control main process according to an embodiment of the present invention.

16B is a diagram illustrating a data management policy establishment process according to an embodiment of the present invention.

16C illustrates a data standard definition process according to an embodiment of the present invention.

16D is a diagram illustrating a data standard evaluation process according to an embodiment of the present invention.

16E is a diagram illustrating a data model operating process according to an embodiment of the present invention.

16F illustrates a data flow management process in accordance with an embodiment of the present invention.

16G illustrates a database operating process in accordance with an embodiment of the present invention.

16H is a diagram illustrating a data utilization management process according to an embodiment of the present invention.

16I illustrates a requirements management process in accordance with an embodiment of the present invention.

<Description of main parts of drawing>

100: DBMS 200: CIO terminal

205: CIO quality control module 300: DA terminal

305: DA quality control module 400: modeler terminal

405: modeler quality management module 500: DBA terminal

505: DBA quality management module 600: user terminal

605: user quality management module

The present invention provides data including at least one or more standard data, model data, management data, and business data, and conceptual data model information, data reference model information, logical data model information, physical data model information, and database corresponding to the model data. A database having information and user view information; Data including at least one or more standard data, model data, management data, and business data; and conceptual data model information, data reference model information, logical data model information, physical data model information, database information, and users corresponding to the model data. At least one quality management module for managing view information according to a predetermined data management process; And at least one terminal for managing the database quality through the quality management module.

Database quality management refers to data management and improvement activities continuously performed to satisfy the expectations of information systems and database users inside and outside an institution or organization, wherein the data management is information performed based on DBMS (Database Management Systems). In terms of management, the main issues involved are data modeling, data architecture, data reference model, and data quality management.

Among the four issues related to the database management, attention has recently been focused on data quality management.

First, as each task of an institution or a company became informatized, serious redundancy and inconsistency between data of sectoral information systems emerged. In addition, in order to effectively support the work and decision making of information system users, an increasing number of organizations have established and operated enterprise-wide data banks and data warehouses that integrate data at the enterprise level. Data quality is causing a lot of problems in system operation.

Second, with the development of the Internet, the integration of external systems as well as system integration within institutions and companies is required, and data standards and data consistency between external organizations and companies to be linked become important issues.

Third, both public institutions and private companies have established customer relationship management (CRM) systems as the beneficiaries of administrative work or customers of business become the most important assets of the organization. The customer relationship management system should not only manage the contracted customer data, but also manage the virtual customer data as well as the data contacted through the call center or internet channel. However, there are many difficulties in managing customer data collected through multiple channels consistently as a single view.

In other words, as the scope and complexity of information systems operated by institutions and enterprises have increased, data quality such as accuracy, redundancy, and consistency has become an important issue, and data quality management is now indispensable for information system operation and management. It is a requirement.

However, the conventional data quality management was left to the database administrator, and thus, data quality management is not matured and includes a problem that a lot of time and cost are consumed.

The present invention is derived to solve the above problems, the data including at least one or more standard data, model data, management data and business data, conceptual data model information, data reference model information corresponding to the model data And a database having logical data model information, physical data model information, database information, and user view information, data including at least one standard data, model data, management data, and business data, and a concept corresponding to the model data. At least one quality control module for managing data model information, data reference model information, logical data model information, physical data model information, database information, and user view information according to a predetermined data management process, and through the quality management module. Database At least one terminal to manage the quality scan; to be provided with a database for the purpose of quality control system, which comprises.

The present invention provides data including at least one or more standard data, model data, management data, and business data, and conceptual data model information, data reference model information, logical data model information, physical data model information, and database corresponding to the model data. A database having information and user view information; Data including at least one or more standard data, model data, management data, and business data; and conceptual data model information, data reference model information, logical data model information, physical data model information, database information, and users corresponding to the model data. At least one quality management module for managing view information according to a predetermined data management process; And at least one terminal for managing the database quality through the quality management module.

According to an embodiment of the present invention, the quality management module manages standard data and conceptual data model information and / or data reference model information included in the database according to a predetermined data standard management process and / or requirement management process. It is preferable that it further comprises.

In addition, the quality management module, preferably further comprises the management of the model data and logical data model information provided in the database according to a predetermined data model management process and / or data flow management process.

In addition, the quality management module, preferably further comprises the management of the management data and physical data model information and / or database information provided in the database according to a predetermined database management process.

In addition, the quality management module, it is preferable to further comprise the management of the work data and the user view provided in the database according to a predetermined data utilization process.

Hereinafter, with reference to the accompanying drawings and description will be described in detail the operating principle of the preferred embodiment of the present invention. However, the drawings and the following description shown below are for a preferred method among various methods for effectively explaining the features of the present invention, the present invention is not limited only to the drawings and description below. In addition, in the following description of the present invention, if it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the subject matter of the present invention, the detailed description thereof will be omitted. Terms to be described later are terms defined in consideration of functions in the present invention, which may vary according to intentions or customs of users or operators. Therefore, the definition should be based on the contents throughout the present title.

In addition, preferred embodiments of the present invention to be carried out below are provided in each system functional configuration to efficiently describe the technical components constituting the present invention, or system functions that are commonly provided in the technical field to which the present invention belongs. The configuration will be omitted, and described mainly on the functional configuration to be additionally provided for the present invention. If those skilled in the art to which the present invention pertains, it will be able to easily understand the function of the components that are conventionally used among the omitted functional configuration not shown below, and also the configuration omitted as described above The relationship between the elements and the components added for the present invention will also be clearly understood.

In addition, the following examples will be used to appropriately modify the terms so that those skilled in the art to clearly understand the technical features of the present invention to effectively understand, but the present invention It is by no means limited.

As a result, the technical spirit of the present invention is determined by the claims, and the following examples are one means for efficiently explaining the technical spirit of the present invention to those skilled in the art to which the present invention pertains. It is only.

1 is a diagram illustrating a database quality management framework structure according to the present invention.

In more detail, FIG. 1 classifies and defines a database quality control object into a data value, a data hierarchy, a data management process, and the like, and defines the subject of database quality management as a user. (600), Database Administrator (DBA) 500, Modeler 400, Data Administrator (DA) 200 and Chief Information Officer (CIO) 200 After the classification and definition as, the database quality management framework structure, characterized in that each database quality management subject to manage the database quality control object corresponding to each data, data structure and data management process. Those skilled in the art to which the present invention pertains can refer to and / or modify the data of FIG. The implementation method of defining the database quality control subject in the ES quality management framework according to the characteristics of each database operation institution may be inferred. Never.

In the database quality management framework shown in FIG. 1, a database quality management subject represents a subject according to a database quality management perspective according to the present invention. For example, a subject managing the database in a general view on the database quality management framework. Corresponds to the chief information officer (CIO) 200, the subject managing the database in a conceptual perspective on the database quality management framework corresponds to the data management officer (DA) 200, the database quality management The subject managing the database in a logical view on the framework corresponds to the modeler 400, and the subject managing the database in the physical view on the database quality management framework is affected by the database manager (DBA). And it will be the subject of managing the database as the database management perspective on quality management framework applicable to the user (600).

The chief information officer (CIO) 200 of the database quality management entities on the database quality management framework is a quality management entity corresponding to the highest layer on the database quality management framework, and manages the database in general terms. , Data management policies and support, and coordination of issues between data managers.

The data management officer (DA) 200 among the database quality management subjects on the database quality management framework is a quality management entity corresponding to a lower layer of the chief information officer (CIO) 200 on the database quality management framework. From the conceptual perspective, the database establishes and operates standards development and configuration management, verification and standardization procedures, integrates enterprise data models, organizes each data requirement, and supports functional data management (Functional Data Management (FDA)). Characterized in that.

A database manager (DBA) 500 among the database quality management subjects on the database quality management framework is a quality management entity corresponding to a lower layer of the data management officer (DA) 200 on the database quality management framework. It is characterized by applying the database to adjust and integrate the data requirements and issues of each functional area from a logical point of view, perform data modeling based on the business requirements of the functional area, and confirm the data standards.

On the database quality management framework, the user 600 among the database quality management subjects is configured as a quality management subject at the lowest (or lower level of the database manager (DBA) 500) layer on the database quality management framework. It utilizes data sources, operational data, and analytical data from an operational point of view, and further requests for additional requirements for the data and increases the utilization of the data.

In the database quality management framework, the data of the database quality management object refers to computerized data used for achieving the vision or goal of the database management organization and the enterprise, or data necessary for computerization, and the data is the database. Standard data managed by a data management officer on a quality management framework, model data managed by a modeler 400 on the database quality management framework, and management managed by a database manager (DBA) 500 on the database quality management framework. Data, and business data managed by the user 600 on the database quality management framework.

In the database quality management framework, the data structure of the database quality control object is a shape and a frame in which the data is stored on the database, and the structure is changed according to the viewpoint of handling the data. For example, forms, reports, screens, forms, etc.), models (e.g., outlines, concepts, references, logic, physics), database files, and the data structure is the database quality management framework. Conceptual data models and data reference models managed by the data management officer on the network, logical data models managed by the modeler 400 on the database quality management framework, physical data models and databases managed by the database manager on the database quality management framework. , Prize Including a user view (User View) and so on managed by the user 600 in the database quality control framework, characterized in that formed.

In the database quality management framework, at least one quality management entity included in the database quality management framework may be configured such that the data management process among the database quality management targets may stably maintain and improve the quality of the data and data structures. A process in connection with the data processing, wherein the data corresponding to the database quality control target includes not only the phenomenal value but also the structural value of the data, and the data structure is subdivided into data structures for each aspect of each quality control subject. And a data quality change management process and a data quality improvement process. The data management process corresponds to a data management officer (DA) 200 on the database quality management framework. A data standard management process and a requirements management process, a data model management process and a data flow management process corresponding to a database manager (DA) on the database quality management framework, and a database manager (DBA) 500 on the database quality management framework. And a database management process corresponding to the data management process corresponding to the user 600 on the database quality management framework.

The standard data managed by the data management officer (DA) 200 on the database quality management framework includes terms, domains, codes, and other data related elements used on an information system to which the database quality management framework is applied. It refers to standard related data that is defined and used in common format and contents. It is an essential element to secure data quality of the information system. By defining and managing standard data, it prevents inconsistency and data error and understands the data. In addition, it is characterized in that it is possible to implement a single, standardized information system at the institutional or corporate enterprise level, and to efficiently perform data integration.

A preferred embodiment in which the data management officer (DA) 200 manages the standard data on the database quality management framework is illustrated in FIG.

Here, the management object of the standard data is characterized in that it comprises a standard word dictionary, standard domain dictionary, standard term dictionary, standard code and data standard elements.

According to the implementation method of the present invention, the standard word dictionary for managing the standard data is a dictionary that defines words of the smallest unit that is used in a business or an institution and has a certain meaning. By convention, the same word is used in different meanings (for example, when you take over assets in terms of "argument", "where you give and what you give"), or in a single word. It is desirable to prevent problems such as giving meaning (eg, "processor") to use.

Here, it is preferable that the management criteria for the standard word dictionary of the standard data management object include standardity, referability, generality, representativeness, and the like.

The standard of the management criteria for the standard word dictionary to be managed by the standard data is that the standard word defined in the standard word dictionary is used in the meaning of the dictionary that is used or generally used in the scope of work targeted by the information system. This should include extracting from the language, avoiding too much work or dialects, and minimizing the use of abbreviations.

In addition, the possibility of reference to the management criteria for the standard word dictionary subject to the standard data management includes that the standard words defined in the standard word dictionary can be referred to when defining a new task in the company or institution. .

In addition, the generality of the management criteria for the standard word dictionary subject to the standard data management includes that the standard word defined in the standard word dictionary is not significantly different from the general word so that the general person can understand the meaning of the word. Is done.

In addition, the representativeness of the management criteria for the standard word dictionary subject to the standard data management, the standard word defined in the standard word dictionary may have synonyms, but the words declared as standard words may represent synonyms having similar meanings. It is done to include.

In the method of managing the standard word dictionary of the standard data management object, the standard word is extracted based on entities and attributes managed throughout the enterprise as individual units, and the physical name (English name, English abbreviation name) is based on the logical name (Korean name). And similar terms are managed together, and the standard word dictionary is managed so that the structure of words such as synonyms, synonyms, antonyms, and the like is defined together with individual words.

According to an embodiment of the present invention, the standard domain dictionary of the standard data management object is a dictionary defining a range of values satisfying a condition defined in an attribute of a domain, wherein the standard domain is data used throughout the enterprise. It is desirable to group logically and physically similar types of data in the middle to define the type and length of data belonging to that group.

Here, it is preferable that the management criteria for the standard domain dictionary for the standard data management object include standardity, uniqueness, work orientation, and the like.

The standardization of the management criteria for the standard domain dictionary to be managed by the standard data includes that the standard domain defined in the standard domain dictionary is defined as an attribute that is commonly used at the enterprise level. For example, it is preferable to define and use a standard domain because the account number of the bank does not vary depending on the bank subtask or the financial product.

In addition, the uniqueness of the management criteria for the standard domain dictionary to be managed by the standard data includes managing so that duplicate domains of the same contents among the standard domains defined in the standard domain dictionary are not declared under different names.

In addition, the uniqueness of the management criteria for the standard domain dictionary of the standard data management object includes that each domain defined in the standard domain dictionary is declared and managed to sufficiently reflect the characteristics of the business. For example, it is preferable to express the domain of the bank account number using '-' to indicate a proper meaning rather than defining without '-'.

The method for managing the standard domain dictionary of the standard data management object includes extracting, grouping, and declaring a standardized domain of attributes implemented in the same form in the DBMS 100 among all data attributes or representative attributes managed throughout the enterprise. All attributes should be assigned to any domain, but not to multiple assignments to at least one domain, which domain consists of a plurality of subdomains (composite domains) or one domain to multiple domains. It manages to be used in the same way, and the property and domain are managed to be mapped to each other, and when a new property is added, it is recommended to select and register a domain of the property, and to delete the domain, Only if no attributes are in use It is desirable to manage.

According to an embodiment of the present invention, the standard term dictionary for management of standard data is a dictionary that defines at least one term that is frequently used in a business and includes at least one term defined by combining standard words. Words are individual, but terminology can vary depending on the nature of the task and organization. By defining the standard terminology dictionary, it is possible to minimize problems caused by lack of understanding or confusion when terminology requires communication between different tasks within an institution or an enterprise.

Here, it is preferable that the management criteria for the standard term dictionary for the standard data management object include standardity, generality, work orientation, and the like.

Standardization of the management criteria for the standard term dictionary of the standard data management object may include minimizing enterprise-wide confusion caused by a difference in the use or meaning of terms defined in the standard term dictionary.

In addition, the generality of the management criteria for the standard term dictionary of the standard data management object is such that the terms defined in the standard term dictionary are not defined too much in terms of business, and thus should not be intuitively understood or cause semantic confusion. It is made to include. In other words, terms used differently from the general meaning should be replaced with other terms.

In addition, the work orientation of the management criteria for the standard term dictionary of the standard data management subject, the term defined in the standard term dictionary includes the use of an abbreviation or separately defined in the internal reflecting the task . However, excessive use of abbreviations or the development of new terms should not undermine the understanding of the work.

In the method of managing a standard term dictionary of the standard data management object, the standard term is managed to generate a combination of defined words of a standard word dictionary for a term of an entity and an attribute used throughout the enterprise, and the term dictionary Is defined and managed by dividing into entity term dictionary and attribute term dictionary, and each term has logical name (Korean name) and physical name (English name), and it is desirable to include and manage explanation of term scope and qualification form. Do.

According to the exemplary embodiment of the present invention, the standard code for the standard data management object means that the standard code is replaced with a symbol within a limited range according to a standard defined for shaping various data values. Codes that are defined and used internally by organizations or companies are targeted, as well as codes that are legally and systematically assigned by industry and commonly used.

Here, it is preferable that the management criteria for the standard code of the standard data management object include reusability, consistency, uniqueness and information analysis.

The reusability of the management criteria for the standard codes subject to the standard data management is higher than that of the standard organizations, the government, and the public rather than the codes defined by the institutions or enterprises themselves in order to improve understanding of the data and to facilitate the code management. This includes the use of code defined by the organization.

Consistency of the management criteria for the standard code of the standard data management object includes that the code corresponding to the standard code is used consistently with a single value. For example, 'Y / N' or '1/0', etc. should not be used in combination.

In addition, the uniqueness of the management criteria for the standard code of the standard data management object includes that the code corresponding to the standard code is defined uniquely. If the work code is duplicated, it can cause serious problems of inconsistency with data at the enterprise level.

In addition, the information analysis of the management criteria for the standard code to be managed by the standard data includes encoding and managing all possible data. In other words, the higher the weight of the value entered by referring to the code than the value directly entered as text, the easier it is to obtain valuable results when analyzing information.

The method for managing the standard code of the standard data management object is to analyze the code that is used throughout the enterprise and the standardization code of the standardization organization or the government and public institutions to determine whether to use the standardization code, and the code is standardized. Should be managed by the team according to strict standards and should not be created or modified by the user 600 arbitrarily, and the code should be closely related to the domain, but the range of values is clearly defined in the domain. (E.g., whether or not 'is indicated by' Y / N ') is preferably managed so as not to code and manage.

According to an embodiment of the present invention, the data standard element of the standard data management object means a standard for data related elements required to design and build a system, and the data related element standard object is a subject area of a logical data model. Naming conventions such as entity, attribute relationship names, physical object target Subject Areas, Relationships, Database & Instances, Indices, Constraints, Sequences, Custom Procedures & Functions, Synonyms, Views, Rollback Segments, Tablespaces, File Names, Script Names, etc. Include.

The system operation may have a mixture of essential elements necessary only for operating the system and elements generated by the system operator. The management criteria for the data standard elements subject to the standard data management include the essential elements required for the system operation. It is made to include.

For example, elements that simply load the result of the program execution are necessary for backtracking when problems occur, but are not essential elements of system operation, and selection criteria of the management target among the data related elements are essential elements for system operation. Be able to be the primary target.

The method for managing data standard elements of the standard data management object includes managing to accurately select elements necessary for operating the system, extracting elements necessary for the design and construction of the system, and defining elements for which standards are required. It is desirable to manage to define business standards for the organization.

The model data managed by the modeler 400 on the database quality management framework refers to data required for operating and managing a data model on an information system to which the database quality management framework is applied. The conceptual data model, the logical data model, metadata about the physical data model, and DBMS 100 object information are included.

A preferred embodiment in which the modeler 400 manages the model data on the database quality management framework is illustrated in FIG.

The model data is characterized by maintaining the latest information on the data structure by managing metadata about the data model, maximizing the sharing and reuse of the data model at the enterprise level, and enables the systematic data model change management.

Here, it is preferable that the management criteria of the model data include completeness, consistency, traceability, correlation, freshness, compatibility, and the like.

Integrity of the management criteria of the model data includes making the model data include metadata for data structures of all stages such as conceptual data models, logical data models, physical data models, databases.

In addition, the consistency of the management criteria of the model data includes that the model data is defined in compliance with words, terms, domains and data standard elements.

In addition, the traceability of the management criteria of the model data, the model data comprises that it is easy to track the change history of the data model and to meet the utilization requirements for the historical data model.

In addition, the correlation between the management criteria of the model data, the model data comprises to represent the inter-relationship between the data models to manage the data structure in a three-dimensional structure.

In addition, the up-to-dateness of the management criteria of the model data includes making the model data logically match not only the business rules expressed in the step-by-step data model but also the database implemented in the actual system.

In addition, the compatibility of the management criteria of the model data includes that the model data is compatible with the standard data and the management data.

In the method for managing the model data, the data structure and the model data representing the structure should be managed separately, and if the data model is changed, the data model before and after the change is, of course, the affected application and SQL (Structured) It is desirable to manage the history of Query Language together.

The management data managed by the database manager (DBA) 500 on the database quality management framework means data required for effectively operating and managing a database on an information system to which the database quality management framework is applied. Includes usage management data, failure and security management data, performance management data, flow management data, and quality management data.

A preferred embodiment in which the database manager (DBA) 500 manages the management data on the database quality management framework is illustrated in FIGS. 13A and 13B.

The management data can be efficiently used and operated by managing data on the use and performance management of the database, data flow management, and quality management based on a target value defined in the organization at any time or a predetermined reference time. It is characterized by that.

According to an embodiment of the present invention, a database can be largely divided into two types, one of which is a database of an operating system that is mainly generated in the course of an institution or a company, and the other of which is analyzed and extracted from the operating system. It is a database of analysis system systems.

The purpose of the management of the operating system database is to ensure the quality of the data itself in order to satisfy the satisfaction of the database users 600, as well as the overall service quality, such as an interface required to efficiently / effectively provide the data. The purpose of management is to increase the utility of the data. In the present invention, the management data will be described focusing on the database of the operating system.

Here, the management target of the management data is characterized in that it comprises use management data, obstacle and security management data, performance management data, flow management data and quality management data.

According to an embodiment of the present invention, the use management data of the management data management object means data to be managed in order to maximize the utilization value of the database and the satisfaction of the user 600.

Here, it is preferable that the management criteria for the use management data of the management data management object include data utilization, user 600 satisfaction, and adequacy of a problem solving time.

The data utilization of the management criteria for the use management data of the management data management object includes periodically identifying the data use trend and analyzing and managing the result trend.

In addition, the satisfaction of the user 600 of the management criteria for the use management data of the management data management object includes determining the satisfaction of the user 600 of the database regularly and analyzing and managing the result trend.

In addition, the appropriateness of the time required for solving the problem of the management criteria for the use management data of the management data management target, the time required for solving the problem by checking the time taken from occurrence of the problem and the time taken to resolve after the problem is confirmed. This involves analyzing and managing how well and systematically the data is managed.

The method of managing the use management data of the management data management target is to aggregate the data change status by daily, weekly and monthly, to analyze the time when a sudden change occurs and to establish the causes and trends, anticipated problems and countermeasures. It manages to analyze problems of database usage and improvement requirements on a regular basis, manages to define various paths to check problems related to the use of the database, and classifies and handles the causes of problems by type. Maintain a detailed record of work and results (problem definitions, related databases, staff and stakeholders, work progress, etc.).

According to the implementation method of the present invention, the management and management data of the management object management data is managed in order to prevent an event that prevents the normal state or effective use of the database in advance or to allow a quick recovery upon occurrence of the event. Means the data to be.

Here, it is preferable that the management criteria for the obstacle and security management data of the management data management object include periodic status records, recovery procedures, rules, and access control.

Periodic status recording of the management criteria for the obstacle and security management data of the management data management includes managing the backup cycle of the database, the backup method, records related to the storage and recovery of the backup data.

In addition, the recovery procedure and rules of the management criteria for the obstacle and security management data of the management data management object is made to define and manage the data recovery procedure and rules applied in an emergency.

In addition, the access control of the management criteria for the management data management object and the management object management data, block access to the database from the inappropriate user 600 inside and outside the database and the authority and level of the user 600 It consists of including to manage.

The method for managing the management data and the management data of the management data management object is to evaluate the database to determine the importance, and to classify the data to be backed up daily, weekly and monthly according to the importance, and the database Establish and periodically train backup and recovery procedures for the system, and ensure that the application rules are as detailed as possible, and that there are no duplications or inconsistencies, and that the location of the backup data should be such that the network and servers are separated from other systems and It manages to set up, establishes security regulations for the database, and periodically trains and promotes, specifies the access rights of the user 600 for each database, and manages to check and act on illegal access periodically.

According to the method of the present invention, the performance management data of the management data management object means data to be managed in order to improve the performance of the database.

Here, it is preferable that the management criteria for the performance management data of the management data management object include a performance improvement procedure, a performance check cycle, and the like.

The performance improvement procedure of the management criteria for the performance management data of the management data management target includes defining and managing procedures and rules for improving the performance of the database in order to systematically manage the performance of the database.

In addition, the performance check cycle of the management criteria for the performance management data of the management data management target includes that the performance measurement criteria and measurement cycles of the database are defined so as to periodically check the performance of the database.

The method for managing performance management data of the management data management target may define performance measurement criteria for the database, manage all the criteria to be quantified, measure performance per day, weekly, monthly, and analyze the trends. Manages and maintains procedures and rules (eg, query optimization, database structure change, etc.) and procedures for improving the performance, and manages to define when and how to reconstruct the database according to the database management. It is desirable to manage to define rules for when to replace and expand the storage of the database.

According to the method of the present invention, the management data management target flow management data means data for managing mapping information between source data and target data used when moving predetermined information system data to another information system.

Here, it is preferable that the management criteria for the flow management data of the management data management object include a mapping rule of source and target data, a source and target data refinement rule, and the like.

And a mapping rule of the source and target data of the management criteria for the flow management data of the management data management object, defining all the sources and targets requiring the data movement, and defining mapping rules between the source targets.

In addition, the source and target data refining rule of the management criteria for the flow management data of the management data management target, the cleansing rules for the data that is in compliance with the defined source and target mapping rules and violate the definition is defined. It is done to include.

The method for managing flow management data of the management data management object includes creating a mapping list between the source data and the target data for the database, and managing to check whether all the source data required by the target system are included. It is managed to check whether a source and a target which do not require data movement are not mapped, and is managed to check whether the deleted source is used as a mapping source, and examines whether the data structure of the source and the target is the same. If it is not the same, it is desirable to manage to apply the conversion rule, to check that the conversion rule conforms to the data integrity rules, and to check whether the result ensures data integrity.

According to the exemplary embodiment of the present invention, the quality management data of the management data management object means data to be managed basically in order to secure the consistency of the data and to perform operations for maintaining and improving data quality. By managing the quality control data, it is possible to prevent inefficient use of the data and to prevent data quality degradation due to data inconsistency that may occur during operation of the data, thereby maintaining high quality data of the entire operating system.

Here, it is preferable that the management criteria for the quality management data of the management data management object include a quality standard, a quality inspection cycle, a quality verification procedure and rules, and a quality improvement procedure.

The quality standard of the management standard for the quality management data of the management data management object defines the quality standard of the data managed by the system. Quality standards include the management of ratings based on the importance of the data.

In addition, the quality check cycle of the management criteria for the quality management data of the management data management target, to set the measurement cycle for the database performance and data quality, etc. to continuously and regularly perform the data quality management. Quality check cycle is made to include the determination to reflect the level of the user 600 requirements.

In addition, the quality verification procedure and rules of the management criteria for the quality management data of the management data management object define data quality verification procedures and rules for applying the defined quality criteria. This includes ensuring that actions taken against exceptions that do not follow the defined procedures and rules are also considered.

In addition, the quality improvement procedure of the management standards for the quality management data of the management data management target, to reflect the measured quality evaluation results to improve the quality of the data and to define a procedure and method for maintaining high quality data It is made to include.

The method for managing the quality management data of the management data management target may include, for example, an entity requiring data quality control for the database (eg, entity entity, referential integrity, domain integrity, attribute, column business rule application, entity, table definition). Data creation, change, deletion rules, triggers, etc. to manage the operation of user-defined DBMS (100) objects, and when data replication is allowed, etc.) It is advisable to manage to define error correction rules for nonconforming data.

The work data managed by the user 600 in the database quality management framework refers to data necessary for performing the work and business of an institution or an enterprise, and can generally be classified into source, operation, and analysis data according to the data flow. have.

The business data is characterized by improving the efficiency of data management and database construction by appropriately partitioning and managing data, which is the basis of information system information, according to each characteristic such as source, operation, and analysis data.

Here, the management target of the business data is characterized in that it comprises a source data, operational data, analysis data, and the like.

According to the method of the present invention, the source data of the business data management object is real world data that is a source of the operation data, and the source data includes a general document, a data source file stored in a PC, an e-mail and a fax, etc. This includes.

Here, it is preferable that the management criteria for the source data of the business data management object include the security of the source data, the safety of the source data, the reliability of the source data, and the like.

The security of the source data of the management criteria for the source data of the business data management target, the source data is not managed systematically by the system, program, or database object, there is a high risk of exposure to unauthorized users 600. Therefore, in the case of important source data, it involves including paying special attention to security.

In addition, the safety of the source data of the management criteria for the source data of the business data management target, because the source data has a high data loss rate in the event of a disaster and the recovery of the lost source data is very difficult, the level of safety management for the important source data This is to keep it high.

In addition, the reliability of the source data of the management criteria for the source data of the business data management subject includes the definition of the basis for this to determine the accuracy and reliability of the source data.

In the method of managing the source data of the business data management object, the source data is managed by the individual or the organization of the source business data owner rather than by the integrated system, the retrieval of the source data is generally the data stored in the system Since it may take more time than searching, it is desirable to manage to define the management system clearly, and to classify the source data necessary for the database construction and define the access authority and creation, change, and destruction rules for each source data. Do.

According to the implementation method of the present invention, the operation data of the business data management object means data that is stored and managed in a database for use in achieving a goal of a company or an institution and performing a job, wherein the data is temporarily used for simple input / output work processing. Exclude temporary data needed.

Here, it is preferable that the management criteria for the operation data for the business data management object include accuracy, consistency, up-to-dateness, completeness, ease of use, ease of search, and the like.

The accuracy of the management criteria for the operation data of the business data management object includes storing and managing the same data as the source data existing in the real world.

In addition, the consistency of the management criteria for the operational data of the work data management subject includes the data to be consistent with the term definition, regulation, standard, attribute definition, data format and the like.

In addition, the freshness of the management criteria for the operational data of the business data management subject is made, including the data provided to be updated with the most recent content, to maintain the freshness of the data to the latest grade (Very important, important, moderate).

In addition, the completeness of the management criteria for the operation data of the work data management object, including the data stored in the information system is provided in a complete form without missing items.

In addition, the ease of use of the management criteria for the operation data of the business data management target, interface, help, customer support functions, etc. provided by the information system is to be provided so that the user 600 is not inconvenient to use the database. It is made to include.

In addition, the ease of search of the management criteria for the operation data of the business data management target, it is to ensure that the search results and output method according to the search-related functions and search conditions to be accurate and appropriate so that the desired data can be extracted and utilized in the information system It is made to include.

The method for managing the operational data of the business data management subject periodically checks and manages data according to defined management standards and management methods to ensure the accuracy, consistency, freshness and completeness of the data, and the ease of use. And searchability should be managed to follow the management criteria and management methods of performance management data.

According to an embodiment of the present invention, the analysis data of the business data management object refers to data generated through a process of extracting, transforming, and loading operational data. To ensure that organizations can quickly support the work or activities of an organization or organization, they must be up-to-date and accurate.

Here, it is preferable that the management criteria for the analytical data for the business data management object include an analysis cycle, a deadline, a summary level, subject orientation, integration, time series, and non-volatility.

The analysis cycle of the management criteria for the analysis data of the business data management object includes determining an analysis and conversion cycle of the operation data which is a source of the analysis data.

In addition, the deadline of the management criteria for the analysis data of the business data management object includes defining a specific time point of the operation data used to convert the operation data into analysis data.

In addition, the summary level of the management criteria for the analysis data of the business data management object defines the summary level required for the analysis data. The level of summarization involves taking into account the scope and depth of operational data.

In addition, the subject orientation of the management criteria for the analysis data of the business data management object is made to include classifying the distributed and managed operational data by a unified subject area.

In addition, the integration of the management criteria for the analytical data of the business data management object comprises the classification of the analytical data according to the same and consistent standard ('male / female', '1/0'). .

In addition, the time series of the management criteria for the analytical data for the business data management object is made to include defining the data accumulated for a predetermined time for various time points.

In addition, the non-volatility of the management criteria for the analytical data of the work data management object includes that the deletion or update of the data does not occur frequently.

The method of managing the analysis data of the business data management object, manages to define a rule for extracting, converting, and loading the operation data into the analysis data, wherein the analysis period, deadline, summary level, etc. are the size of the analysis target data B. It should be managed to define it in consideration of characteristics, purpose of use, etc.

The conceptual data model managed by the data management officer (DA) 200 on the database quality management framework includes a subject area and a core data set of data meeting the business requirements of an information system to which the database quality management framework is applied. A model is defined, and a relationship between each other is defined. A preferred embodiment of the conceptual data model is shown in FIG.

The conceptual data model draws the core data structure of the business model to be constructed, such as a bird's eye view of the building, and is characterized in that it can take a large outline of the whole work and proceed to the detailed steps.

In addition, the conceptual data model supports the data structure alignment between the detailed logical data model and the physical data model, which will be defined in the future by defining a relationship between a subject area and a core data set suitable for the characteristics of an institution or an enterprise. In addition, it is characterized in that the subject area allows the user to check the entire scope of work and work components.

Here, the management target of the conceptual data model is characterized in that it comprises a subject area, a core entity, and a core relationship.

According to the method of the present invention, the subject area of the conceptual data model management object means a data set having high business intimacy.

Here, it is preferable that the management criteria for the subject area to be managed by the conceptual data model include atomicity, concentration, and work orientation.

The atomicity of the management criteria for the subject area subject to the conceptual data model management is that a predetermined unit subject area includes a group of entities which are not affected by the entities or relationships of other subject areas as much as possible.

In addition, the centralization of the management criteria for the subject area subject to the conceptual data model management may include causing the relationship with the entities in the unit subject area to be concentrated in the unit subject area.

In addition, the task orientation of the management criteria for the subject area to be managed by the conceptual data model includes naming the subject area in a singular unit representing business clarity.

The method for managing subject areas of the conceptual data model management object includes declaring entity sets as one subject area that is more effective to handle in the same work area, and managing the subject areas to be divided into several types according to work diversity. In addition, although the scope of clearly distinguishing tasks may be defined as one subject area, it is desirable to manage the number of entities shared between different subject areas as much as possible.

According to an embodiment of the present invention, the core entity of the conceptual data model management object is a data set to be managed in the business area, and should have two or more attributes and two or more data instances. It is a homogeneous, independent data set and corresponds to a data unit that exists permanently. Among them, the key entity, the core entity, which is the main entity, is a high-level entity that is the basis of a task and can create a number of child (task, transaction) entities.

Here, it is preferable that the management criteria for the core entity subject to the conceptual data model management include aggregation, identification, persistence, usability, relationship, and the like.

The aggregation of management criteria for the core entity subject to the conceptual data model management comprises the entity consisting of a set of data having two or more attributes and two or more data instances.

In addition, the identification of management criteria for the core entity subject to the conceptual data model management comprises the entity being able to uniquely distinguish each data instance of the entity by one or more attributes.

In addition, the persistence of the management criteria for the core entity subject to the conceptual data model management is a data set that must exist permanently according to the activity cycle of the task, and the data that must disappear or be generated when the contents of the task are changed. Aggregates are inappropriate for declaring and managing as such entities.

In addition, the usability of the management criteria for the core entity subject to the conceptual data model management is a data set that must be used within the scope of business, and if declared but not used, there is no value as an entity.

In addition, the relationship between the management criteria for the core entity to be managed in the conceptual data model includes that the entity must have a relationship with another entity, and an entity without a relationship may be an unused entity. Violation of usability.

The method of managing the core entity of the conceptual data model management object is that the entity is managed to be collected from a document, a journal, an interview, a related technical book, a DFD, another system, a report, a field survey, and the entity is logical. Declare it correctly by dividing it into units, but manage it so that one entity looks semantically different so that it is not duplicated (i.e. if one entity looks different depending on its state, identify the homogeneity of the data and declare it as one entity as a subtype). Should be managed).

According to an embodiment of the present invention, the core relationship of the conceptual data model management object represents a logical relationship between the core entities, and the business rule that influences the existence form or mutual influence of the entities in the present or near future. It expresses a useful relationship in a limited way, and has a relationship name, an optional specification, and a relationship type. In the relational data model, the relationship must exist between entities.

Here, it is preferable that the management criteria for the core relationship of the conceptual data model management object include selectivity, formability, work orientation, and the like.

The selectivity of the management criteria for the core relationship of the conceptual data model management object includes the relationship that can be expressed by distinguishing between "essential" and "selection".

In addition, the form nebula of the management criteria for the core relationship of the conceptual data model management object, the relationship is made to include the definition (degree) of 1: 1, 1: M, N: M to be managed.

In addition, the work orientation of the management criteria for the core relationship of the conceptual data model management object clearly indicates how the relationship between the two entities affects each other (ie, the existence of an instance of a child entity must If the existence of the parent instance is required but the existence of the child instance is not affected, then the relationship may be made to clearly express the effect of the existence between such parent and child entities.

In the method for managing the core relationship of the conceptual data model management object, the core relationship may maintain the M: M relationship as it is in the conceptual data model step, and manage the M: M relationship to include the resolved entity. The relationship name between parent and child must be defined to be defined, and the relationship name must be specific, and the relationship between the parent (parent) and the receiver (child) between entities must be clearly defined, and the data having the relationship must exist. It is preferable to manage so that selectivity for the case where there is no target data having a relationship with the case, and manage to be able to clearly express the form of the relationship between the predetermined data and one or more data.

Referring to FIG. 1 according to an embodiment of the present invention, an overview data model may be placed on top of the conceptual data model according to the intention of a person skilled in the art, wherein the overview data model may include a data area and a data set in a work area. Defined from an enterprise-wide perspective, but not limited to, and / or each data region has a relationship with other data regions, and / or more primized attributes that are commonly used in the public interest rather than the interests of an institution or company. It is possible to define at the level of shape, a preferred embodiment of the general data model is shown in FIG.

The data reference model managed by the data management officer (DA) 200 on the database quality management framework is used between organizations for the construction and maintenance of the data architecture of the information system to which the database quality management framework is applied. It refers to a data model that defines a standard data set and management items for each work area and subject area for the purpose of interoperation of data models and reference and reuse of other organizational data models. A preferred embodiment of the data reference model is a drawing. 5 is shown.

The data reference model may save time required for overall modeling by securing basic information in advance when modeling new data.

In addition, the data reference model may prevent the loss of information by using the data reference model when modeling new data.

In addition, the data reference model may identify or supplement an error of the company's data model using a previously verified data reference model.

In addition, the data reference model can improve the quality of the lower institution or department data model in a short time by adopting a high quality data reference model in the central organization or department.

The management target of the data reference model is a reusable data model. The attribute reference unit, entity, and entire business area unit may also be a data reference model. Conceptual data models, logical data models, and physical data models can also be scopes of data reference models.

Here, it is preferable that the management criteria for the data reference model include generality, simplicity, standardity, accuracy, information availability, and classification.

The generality of the management criteria for the data reference model includes information on specific data of a specific task, and defines and manages something that can be referred to in various work areas in general.

In addition, the simplicity of the management criteria for the data reference model includes not limited to a specific task so as to maximize the utility.

In addition, the standard of the management criteria for the data reference model includes the data term being expressed to maximize the reference usability of the data model using terms that can be understood at a common sense and general level.

In addition, the accuracy of the management criteria for the data reference model includes that the information to be managed is accurate only as a model having the nature of reference.

In addition, the information availability of the management criteria for the data reference model includes not only the relationship between the entities, but also includes storing and referencing the definition of the entity and the entity, the data management rules of the entity, and the attribute.

In addition, the classification of the management criteria for the data reference model is made to be classified not only within the work area and industry, but also within each step of the data structure and the scope of the data reference model.

The method for managing the data reference model is preferably defined in a central organ or upper organization and managed to be shared and shared by the lower organ or organization.

The logical data model managed by the modeler 400 on the database quality management framework is a model that defines a logical data set, management items, and relationships by detailing a conceptual data model of an information system to which the database quality management framework is applied. A preferred embodiment of the logical data model is shown in FIG.

The logical data model is the most important model in the overall data structure, and can identify the entire work scope and work components.

In addition, the logical data model can prevent unnecessary data duplication and data inconsistency by defining and managing data in detail in the step.

According to an embodiment of the present invention, terms expressing entities, attributes, and relationship names in the logical data model are defined within standard words and standard terms specified in standard data, and the current tasks are specifically reflected in the logical data model. If the object of the physical data model or the database is changed but the change is not reflected in the logical data model, the accuracy of the logical data model is inferior and the quality of the managed data is affected. It also manages the history for, and if the history is managed can be returned to the logical data model of a certain point in time in the past according to the matter.

Here, the management object of the logical data model is characterized by including a subject area, an entity, a relationship, an attribute, and the like.

According to an embodiment of the present invention, the subject area of the logical data model management object is to declare and manage a data set having high business intimacy as one subject area.

Here, the management criteria for the subject area of the logical data model management object, the subject area management criteria and method of the logical data model preferably follows the concept data model subject area management criteria.

According to an embodiment of the present invention, the entity of the logical data model management object may include sub-type information including a definition of a conceptual data model and in which history management, homogeneity, and independence information are identified in more detail.

Here, it is preferable that the management criteria for the entity to be managed by the logical data model include perfection, permanence, identification, homogeneity, normalization, and the like.

The integrity of the management criteria for the entity subject to the logical data model management comprises maintaining two or more attributes and two or more instances in the respective data set.

In addition, the persistence of the management criteria for the entity to be managed by the logical data model may include a data set that is currently managed or a data set that will be managed in the future.

In addition, the identification of the management criteria for the entity to be managed by the logical data model includes making one or more attributes exist that can individually distinguish instances of the entity.

In addition, the homogeneity of the management criteria for the entity to be managed by the logical data model allows the entity that is a predetermined data set to include a data set in which homogeneous data is collected.

The normalization of the management criteria for the entity subject to the logical data model management includes generally allowing the entity to be normalized up to the third normalization.

The method of managing the entity to be managed by the logical data model follows the method of managing the conceptual data model, and it is preferable to add and manage detailed information such as an entity definition and a data generation rule according to the detail of the information.

According to the exemplary embodiment of the present invention, the relationship of the logical data model management object includes the definition of the conceptual data model, and means that all M: M relationships are resolved in the detailed logical data model step.

Here, it is preferable that the management criteria for the relationship of the logical data model management object include the selectivity, the relationship type, the relationship name, and the like.

The selectivity of the management criteria for the relationship of the logical data model management subject includes making the relationship be divided into mandatory and optional, and the mandatory relationship must have an instance with the relationship present in the entity. Means.

In addition, the relationship form of the management criteria for the relationship of the logical data model management object includes that the relationship can have a relationship of 1: 1 or 1: M, M: N.

In addition, the relationship name of the management criteria for the relationship of the management object of the logical data model may be omitted in the expression when the relationship is clear, but in general, it is necessary to have a relationship name when establishing the relationship between the entities. It is made to include.

The method of managing the relationship of the logical data model management object is managed to follow the method of managing the conceptual data model, and it is preferable to define and manage the business rules contained in the relationship in detail.

According to an embodiment of the present invention, the attribute of the logical data model management object means information items to be managed in an entity.

Here, it is preferable that the management criteria for the attributes of the logical data model management object include atomicity, consistency, integrity, informationality, and the like.

The atomicity of the management criteria for the attributes to be managed by the logical data model should be divided into meaningful minimum units, and one attribute includes information of several states at the same time.

In addition, the consistency of the management criteria for the attributes of the logical data model management object, the predetermined attribute is made to include one data type and manages only one data.

The integrity of the management criteria for the attributes of the logical data model management object includes making the data of the referenced attribute match the data of the attribute referring to the attribute.

The informationality of the management criteria for the attributes of the logical data model management object includes making the level of detailing determined within a meaningful range within the task.

The method for managing an attribute of the logical data model management object includes managing the attribute so that it is not indiscriminately increased according to a request of the user 600 after it is initially determined within a management item range of an entity, and the attribute is existing information. When it is not possible to extract from, it is desirable to manage the addition so that it can be added and the entity can be added according to the specification of the attribute.

The physical data model managed by the database manager (DBA) 500 on the database quality management framework is a physical data model in consideration of the characteristics and performance of the DBMS 100 of the information system to which the database quality management framework is applied. This means a model in which the preferred embodiment of the conceptual data model is shown in FIG.

The physical data model is defined after the DBMS 100 is selected, and the DBMS 100 is designed and managed to ensure the best performance and reflect the physical characteristics of data stored in the physical data model to the maximum extent.

In addition, since the physical data model is not an actual data object, it may be neglected, but since the physical data model is not declared as a database object in 1: 1, it should be managed with importance.

In addition, in the physical data model design step, sample data may be used to re-verify the consistency of the physical data model.

In addition, in order to design the physical data model, a user screen must be completed according to business requirements and needs, so that the physical data model can be designed under mutual verification with user applications.

According to the implementation method of the present invention, the design time of the physical data model is the stage at which the design of the application and the business requirements are clear, and it is preferable that the physical data model reflecting the business requirements is designed. It is preferable to declare and create a physical name based on the standard words and standard term rules specified in the standard data based on the standard words and column names.In the physical data model, the declaration of the domain is important and faithful adherence to the domain rules. Will be a prerequisite to maintaining high quality of data maintained within the physical data model.

Here, the management target of the physical data model is characterized by including a subject area, a table, a relationship, a column, and the like.

According to an embodiment of the present invention, the management criteria for the subject area of the physical data model management object may be that one subject area defined in the logical data model is distributed to different schemas or servers in the physical data model. In some cases, a physical subject area may be managed according to a naming convention of a table in one schema of one server. The subject area management criterion of the physical data model preferably conforms to the criteria of the conceptual data model and the logical data model. The method of managing the subject area of the logical data model management object may include the logical subject area and the instance of the DBMS 100. And managing the correspondence with the schema.

According to an embodiment of the present invention, the physical data model management target table is divided into one or more physical tables according to one table or subtype or business characteristic according to the physical characteristics of the data and the characteristics of the DBMS 100. Can be.

Here, it is preferable that the management criteria for the table to be managed by the physical data model include permanence and identification.

The persistence of the management criteria for the table to be managed by the physical data model includes data that is currently managed by the data in the table and needs to be managed in the future.

In addition, the identification of the management criteria for the table of the physical data model management object comprises the record in the table to be distinguishable by one or more column data.

In the method for managing a table to be managed in the physical data model, it is preferable to manage design information such as the life cycle of the data stored in the table and the amount of data to be maintained and managed for a certain period of time.

According to an embodiment of the present invention, the relationship between the physical data model management object means a rule for creating, deleting, and changing data between a parent table and a child table.

Here, it is preferable that the management criteria for the relationship of the physical data model management object include a generation rule, a change rule, a deletion rule, and the like.

The generation rule of the management criterion for the relationship of the physical data model management object includes that the data referred to the parent table must exist when the data of the child table is generated.

In addition, the rule of changing the management criteria for the relationship of the physical data model management object is that, if the key data of the parent table is changed, the reference data of the referenced child table is also changed or if the child data exists, the key data of the parent table. This includes preventing the change.

The deletion rule of the management criteria for the relationship of the physical data model management object is that when the data of the parent table is deleted, the data of the child table referencing the data is deleted together or the data of the parent table is deleted if the child data exists. It may not be possible.

In the method for managing the relationship of the physical data model management target, the relationship is a business rule, so that the management is to determine whether to manage at the DBMS (100) level or at the application level first, the automatic change by the trigger is DBMS (100) Since it is difficult to track in case of error, it is desirable to manage it to minimize it as much as possible.

According to an embodiment of the present invention, the column of the physical data model management object is defined so that data reflecting a business rule can be stored in a standardized domain.

In the method for managing a column to be managed in the physical data model, predetermined column data is managed to have the same data type and data representation, and the physical attribute of a column having a similar data type and expression is defined as a domain and managed. It is desirable to.

The database managed by the database manager (DBA) 500 on the database quality management framework is a result of implementing a physical data model of an information system to which the database quality management framework is applied, and stores data on which actual data is stored. Means a repository, the table code of the database is shown in Figure 8, and the database created thereby is shown in Figures 9a and 9b.

The database can be effectively operated by defining and managing the database storage table, an index for ensuring access speed, constraints reflecting business rules, and other database related objects.

Here, the management target of the database is characterized in that it comprises a storage space, tables, constraints, indexes, triggers, DB links, procedures, views, synonyms, and roles.

According to an embodiment of the present invention, the storage space of the database management object refers to an area (tablespace, data file) defining a table and an index requiring a space for storing data in the database, and operating in the database. All data is divided into tables and indexes, and data management begins with the management of storage space.

Here, it is preferable that the management criteria for the storage space of the database management object include safety, security, scalability, and performance guarantee.

Safety of the management criteria for the storage space of the database management object is made, including the disk area of the system for the storage space to be secured separately from other program execution area of the system, for this purpose, a normal work system Since the DBMS 100 operates a dedicated server, and / or the storage space is a real space in which the data is physically stored, the existence of the storage space is protected from an external threat or disaster.

In addition, the security of the management criteria for the storage space of the database management object, so that the storage space is a real space where the data is physically stored to allow complete access control to unauthorized programs or users 600.

In addition, the scalability of the management criteria for the storage space of the database management object includes the expansion of the storage space and the allocation of the physical disk area is sufficient because the data is continuously increased in the storage space.

In addition, the performance guarantee of the management criteria for the storage space of the database management target, since the large amount of data is called and stored from time to time during the operation of the DBMS 100, the physical disk allocated storage space as a product that can maintain fast performance Appropriate structural arrangements are made.

In the method for managing the storage space of the database management target, the DBA checks the storage space of the system from time to time in consideration of performance and security in accordance with management standards, and manages the final security and safety of data for the first purpose, and also the developer In addition, it is desirable to control the data to be expanded indiscriminately according to the convenience of the user 600 and to manage the backup to the appropriate level of storage space.

According to the method of the present invention, the database management target table, entities and attributes are defined as a table in the database, various methods such as clusters, partitions, etc. can be applied according to the characteristics of the data, the increase of the data Depending on the trend, physical properties may change.

Here, it is preferable that the management criteria for the table to be managed by the database include periodicity, diversity, security, and logic.

The periodicity of the management criteria for the table to be managed by the database may be such that data in the table is backed up at regular intervals or regenerated for performance.

In addition, the variety of management criteria for the table to be managed by the database, the data in the table according to the appropriate distribution strategy and table storage space definition method for performance, Partition (Partition), Cluster (Cluster), Index Organized Table (IOT) , Etc., to be defined in several forms.

In addition, the security of the management criteria for the table to be managed in the database, such that the table to access, create, change, delete rules on a table basis, column basis to a limited range of users 600 according to the authority and use It is made to include.

In addition, the logicality of the management criteria for the table to be managed in the database is made, including that the addition of the table and the addition of the column must be performed by reference to a logical data model, not based on the logical data model The addition of tables and columns on the DBMS 100 will yield indiscriminately redundant data, resulting in poor data quality.

The method of managing a table managed by the database is appropriate so that the DBA manages data of the table in consideration of performance and security according to management criteria, and does not indiscriminately create a table in consideration of the convenience of the developer or the user 600. It is desirable to manage to limit it.

According to an embodiment of the present invention, the constraints of the database management target may include business such as Not Null, Default, Foreign Key Constraint, and Check conditions in the database. It is recommended that the rule be defined in the column, but the constraint on applying the relationship between tables means that the rule is applied in parallel with the application.

In this case, the management criteria for the constraints of the database management object include a non null condition, a default, a foreign key condition, a check condition, and the like in the database. desirable.

The not null condition of the management criterion for the constraint of the database management object includes defining a column in which data must exist in the table.

In addition, a default condition of the management criteria for the constraints of the database management object includes defining basic data when a determination value cannot be defined in a column in which the data must exist.

In addition, the foreign key condition of the management criteria for the constraints of the database management object includes defining and managing rules for inputting, deleting, and creating a relationship defined in the physical data model.

In addition, the check condition of the management criteria for the constraints of the database management object includes defining that only data within a predetermined type or range of data exists in a specific column.

In the method for managing the constraints of the database management object, the reflection of the constraints on the column is managed to be consistent with the attribute definition of the logical data model, and the rule about the relationship is managed to be maintained by the application. desirable.

According to an embodiment of the present invention, the index of the database management object is one of the data stores that are not reflected in the logical data model in the database but to speed up data access. Criteria can be defined in various ways according to business requirements. However, the higher the redundancy of the columns, the more wasteful of storage space and adversely affects the speed of data entry, deletion, and update. Various kinds may exist according to the kind of 100).

The method of managing the index for managing the database is generally maintained in the form of B + Tree. In this case, since the index has little reuse of storage space, it is preferable to regenerate the index periodically.

According to an embodiment of the present invention, the trigger of the database management object is to perform a predefined function in association with a table in the database, and the management criterion for the trigger of the database management object is BEFORE upon generation of the trigger. The key can be used to specify that the Tuple (row, record) can be started before an event occurs. On the contrary, the AFTER key can be used to activate it after the event is completed.

In the method of managing a trigger of the database management object, another trigger may be sequentially activated when a trigger is executed. Therefore, the creation and use of triggers must be carefully defined and unwanted results can be obtained by the use of invalid triggers, and one or more triggers can be defined that specify the same event in the same table, but this does not change the triggering sequence of the triggers. Unpredictable and may be omitted by those skilled in the art.

According to an embodiment of the present invention, the DB link of the database management object is to connect a database remote from the database to process data in another server in one server within one SQL statement. The management criteria for DB link of database management target is defined in the distributed server environment when you want to easily call the data of the table located in one server to another server or another database instance.

In the method of managing the DB link of the database management target, since the DB link is properly created but the connection frequently occurs at the time of querying, it is necessary to verify whether the DB link works in actual use, and also the abuse of the DB link. Can slow down the execution of SQL, so it is desirable to properly manage it in consideration of the performance of the information system.

According to an embodiment of the present invention, the procedure of the database management object, the function (Function) and the procedure (Procedure) in the database is defined and used by the user 600, the function and the procedure is written in the program SQL statement The function and procedure can be called by using SQL statement.

The management criteria for the procedure to be managed in the database is that the data of the table is inputted, modified, or deleted by SQL statements, but when performing complex tasks or when the same type of SQL is repeated, This includes the definition of a procedure.

In the method of managing a procedure to be managed in the database, the functions and procedures are managed to increase the reuse rate of functions and procedures defined in another schema by declaring synonyms when publicity is more emphasized. Because the statement can greatly slow down the overall execution speed, it is desirable to manage the statement through performance verification.

According to an embodiment of the present invention, the view of the database management object is an object created to view data in the database, and does not require a physical storage space, and performs the execution result of the SQL statement defined by the user 600. As the virtual data area shown, there may also be a view having actual physical storage space according to the type of commercial RDBMS 100.

The management criteria for the view of the database management target include creating access for important data, reducing database complexity, hiding complex database designs, and simplifying tasks including distributed queries on heterogeneous data.

In the method of managing the database management target view, since the complex view does not properly grasp the intention of the user 600, it is difficult to grasp the work of the SQL performed as a whole, and may affect the speed. It is advisable to manage the use of too complex views.

According to an embodiment of the present invention, the synonym of the database management object means an alias for a table in the database, a general synonym can be created by all users, and ownership can be used only by the creator. As a synonym for PUBLIC, only DBAs can create and delete.

The management criteria for synonyms for the database management subject include defining synonyms for table data defined in another schema when the subject area is defined as a schema, but which should be frequently referred to frequently in business.

In the method of managing a synonym for managing a database, the synonym may be generated when one object is to be sharedly used in multiple schemas. Even if an object created in another schema has read permission, access to the object may not be performed. When it is cumbersome, it is better to use synonyms to simplify management.

According to the method of the present invention, the role of the database management object (Role) means the create, delete, read, change authority rules for the database object, the authority to grant and control the role is a DBA Have

The management criteria for the role of the database management object is that the ease of use is important when managing the database objects, but the security and management of the data in the table are also important. Properly suggesting permissions involves protecting roles in database objects and defining roles to protect data within objects.

The method for managing the role of the database management target, provides a number of basic roles by combining high-priority rights that can be frequently used in the commercial RDBMS (100), the role is basically provided by the commercial RDBMS (100) It is desirable to manage the system to define and use it according to the security rules in the system.

The user view managed by the user 600 on the database quality management framework refers to a screen or output on the information system to which the database quality management framework is applied, and is a preferred embodiment of the user view. Is shown in FIG.

The user view is a result of work performed throughout data quality management, and is the final output provided to the user 600. Therefore, in order to maximize satisfaction with the data, the user view should be developed and managed according to the level required by the user 600.

Here, the management target of the user view is characterized by including a screen and output.

According to the exemplary embodiment of the present invention, the user view management target screen is an interface for providing a final output generated by the information system, and includes an end user screen and a screen for a system administrator.

Here, it is preferable that the management criteria for the storage space of the user view management object include convenience, searchability, system performance, and supportability.

Convenience of the management criteria for the storage space of the user view management target includes making all the work procedures processed through the user screen intuitive and convenient.

In addition, the searchability of the management criteria for the storage space of the user view management target includes the user 600 to quickly and accurately search for the desired information through the screen.

In addition, the system performance of the management criteria for the storage space of the user view management target includes making sure that all operations processed through the screen maintain an appropriate speed and performance (eg, response within 3 seconds).

In addition, the support of the management criteria for the storage space of the user view management target includes the user 600 to use the appropriate help as needed during the job processing.

In the method of managing the screen of the user view management target, it is preferable to manage not only information on the use and constraints of the screen, but also user requirements and help on the screen.

According to an embodiment of the present invention, the output of the user view management object refers to the output generated through the information system, and includes outputs such as reports, documents, slips, etc., as well as an application program for generating the output. . In general, the output is provided to the end user 600 or used for analysis in the information system.

Here, the management criteria for the storage space of the user view management target is an important data storage tool that can store the value of the data in preparation for the damage of the digital data or the recovery in the event of an accident because the paper output is very low Since the management can take a lot of cost and manpower, it is preferable to manage the output of the image in parallel to the management of the paper state as the important information management.

In the method for managing the output of the user view management object, since most of the output is provided through the user screen, managing the screen replaces quality management of the output. However, if there is no user screen, it is preferable to manage the work related to the output generation and the output (for example, the scanned output) through the system management tool.

2 is a diagram illustrating a configuration of a database quality management system according to an embodiment of the present invention.

In more detail, Figure 2 is based on the database quality management framework shown in Figure 1 based on the user (User) 600 (Database Administrator; DBA), Modeler 400 (Modeler), Data Manager ( Quality control subjects including Data Administrator (DA) and Chief Information Officer (CIO) work together to target the quality management targets corresponding to data value and data structure according to the data management process. As a database quality management system characterized in that the management, those of ordinary skill in the art to which the present invention belongs, reference to and / or modifying the Figure 2, the database quality management framework shown in 1 It can be inferred from the configuration of various database quality management system that is operated based on, but the present invention is inferred It includes both upon how and shall not be limited to the exemplary method shown in the figure 2.

For example, the database quality management system shown in FIG. 2 uses the database quality management framework shown in FIG. 1 to determine the quality of at least one or more databases provided in the DBMS 100 in association with a predetermined DBMS 100. The DBMS 100 is implemented in the form of a server system including at least one or more servers to be managed for each quality control entity on the basis of, and / or in conjunction with, a DBMS 100 provided in a predetermined institution and / or an institution. Components included in an enterprise computer system for managing the quality of at least one database provided in each quality control entity based on the database quality management framework shown in FIG. 1 (eg, each institution and / or company). Can be implemented in the form of components included in the ERP system provided in the The present invention will not limited.

Referring to FIG. 2 according to an embodiment of the present invention, the database quality management system includes at least one or more terminals used by at least one quality management entity, and at least one quality management entity in database quality management shown in FIG. It characterized in that it comprises at least one or more quality management module to manage the predetermined DBMS 100 by interworking according to the framework, the quality management module is based on the database quality management framework shown in FIG. It is characterized in that associated with at least one or more DBMS (100) to be managed.

At least one terminal used by at least one quality management entity corresponding to the database quality management framework includes: a CIO terminal used by the chief information officer (CIO) 200 on the database quality management framework; DA terminal used by the data management officer (DA) 200 on the work, modeler 400 terminal used by the modeler 400 on the database quality management framework, and database manager (DBA) on the database quality management framework ( And a user 600 terminal used by the user 600 on the database quality management framework.

Here, each terminal used by the quality control subject on the database quality management framework is not a terminal that is physically classified, but a terminal for each quality management subject on the database quality management framework to access each quality management module. It is made to include.

Each terminal used by the quality control subject on the database quality management framework is a wired network based on Transmission Control Protocol / Internet Protocol (TCP / IP) (eg, Asymmetric Digital Subscriber Line (ADSL) / Very high-data rate). And at least one wired terminal including a desktop computer and / or a notebook connected in communication with the quality management module via a digital subscriber line and / or a cable communication network, and / or Code Division Multiple Access (CDMA). And at least one wireless terminal including at least one mobile communication terminal connected to a mobile communication network based on the base station, and / or a portable internet terminal connected to the IEEE 802.16x based high-speed wireless internet. The terminal may include at least one quality management interface provided by each quality management module. It is preferable that a function configuration (eg, a browser program and a communication function) is provided for outputting an eS screen and for inputting and / or selecting at least one or more information through the QC interface screen. .

Those skilled in the art to which the present invention pertains can easily infer the characteristics of the terminal corresponding to at least one or more wired terminals and / or wireless terminals, and thus a detailed description thereof will be omitted for convenience.

According to the implementation method of the present invention, each terminal used by the quality control subject on the database quality management framework is characterized in that access to each quality control module through a predetermined interface means.

For example, the database quality management system may control the quality of at least one or more databases included in the DBMS 100 in association with a predetermined DBMS 100 based on the quality management framework of the database shown in FIG. When including a server system including at least one or more servers to be managed by each subject, the interface means may comprise a wired or wireless communication network (or communication means) connecting the terminal and the server.

Alternatively, the database quality control system may determine the quality of at least one or more databases provided in the DBMS 100 in connection with a DBMS 100 provided in a predetermined institution and / or an institution. In the case of including a component included in an enterprise computer system (eg, a component included in an ERP system provided in each institution and / or company) to manage each quality management entity based on a framework, the interface means It may include a wired and wireless communication network (or communication means) connecting the terminal and the enterprise computer system and the enterprise computer system accessed by the terminal.

The CIO terminal 200 used by the chief information officer (CIO) 200 among the quality control subjects on the database quality management framework is characterized in that access to the CIO quality management module 205 through a predetermined interface means, The CIO quality management module 205 establishes a communication channel for database quality management for the DBMS 100 based on the CIO terminal 200 and the database quality management framework shown in FIG. 1 through the interface means. It is characterized by comprising an interface unit 215 to connect and manage.

According to an embodiment of the present invention, when the CIO terminal 200 is a wired terminal, the interface unit 215 has a predetermined communication channel based on the CIO terminal 200 and the Hyper-Text Transfer Protocol (HTTP) protocol. Through the communication channel, and transmits and outputs a quality control policy setting interface screen and / or an information providing screen in the form of a Hyper-Text Markup Language (HTML) compatible document to the CIO terminal 200 and outputs the same. It is preferable to perform a function of receiving and processing predetermined quality management policy information inputted (or selected) through the quality management policy setting interface screen from 200.

According to another embodiment of the present invention, when the CIO terminal 200 is a CDMA-based wireless terminal, the interface unit 215 may connect to the CIO terminal 200 and a WAP (Wireless Application Protocol) and / or ME (Mobile). Connect a predetermined communication channel based on the explorer protocol, and through the communication channel, the quality management policy setting interface screen and / or information in the form of a wireless markup language (WML) and / or HTML compatible document to the CIO terminal 200. It is preferable to perform a function of transmitting and outputting a provision screen and receiving and processing predetermined quality management policy information corresponding to the quality management policy setting interface screen from the CIO terminal 200.

According to another embodiment of the present invention, when the CIO terminal 200 is an IEEE 802.16x based wireless terminal, the interface unit 215 may be a wireless protocol corresponding to the CIO terminal 200 and the IEEE 802.16 standard. Connect a predetermined communication channel based on the above, transmit a predetermined quality management policy setting interface screen and / or information providing screen to the CIO terminal 200 through the communication channel and outputs, and from the CIO terminal 200 It is preferable to perform a function of receiving and processing predetermined quality control policy information corresponding to the quality control policy setting interface screen.

Referring to FIG. 2, the CIO quality management module 205 interoperates with the interface unit 215 to input (or select) predetermined quality management policy information from the CIO terminal 200 and transmit the predetermined quality management policy information. A UI processing unit 225 for generating (or extracting) a quality management policy setting interface screen and an input (or) from the CIO terminal 200 through the quality management policy setting interface screen in cooperation with the interface unit 215. And a policy setting unit 220 for receiving the quality control policy information to be transmitted) and storing the received quality control policy information in a predetermined storage medium.

When the predetermined CIO terminal 200 approaches the CIO quality management module 205 through the interface unit 215, the UI processing unit 225 includes a functional configuration (eg, CIO) provided in the CIO terminal 200. A predetermined quality management policy setting interface capable of inputting (or selecting) predetermined quality management policy information corresponding to a browser program provided in the terminal 200 and transmitting it to the CIO quality management module 205 through the network means. The CIO terminal generates a screen, and / or extracts from a predetermined DB (not shown), and the quality management policy setting interface screen generated (or extracted) in conjunction with the interface unit 215 through the network means. Characterized in that provided by 200.

Thereafter, the CIO terminal 200 inputs (or selects) predetermined quality management policy information based on the quality management policy setting interface screen, and inputs the input (or selected) quality management policy information through the network means. Send to the CIO quality management module 205.

The policy setting unit 220 inputs (or selects) predetermined quality control policy information through the quality control policy setting interface screen in the CIO terminal 200 and provides the same through the interface means. And the quality control policy information in conjunction with the control unit. The received quality control policy information is stored in a predetermined storage medium provided in the CIO quality management module 205.

The DA terminal 300 used by the data management officer (DA) 200 among the quality management subjects on the database quality management framework, accesses the DA quality management module 305 through a predetermined interface means, The DA quality management module 305 establishes a communication channel for database quality management for the DBMS 100 based on the database quality management framework shown in FIG. 1 and the DA terminal 300 through the interface means. Characterized in that it comprises an interface unit 310 for connecting and managing.

According to an embodiment of the present invention, when the DA terminal 300 is a wired terminal, the interface unit 310 is a predetermined communication channel based on the Hyper-Text Transfer Protocol (HTTP) protocol with the DA terminal 300. To the mobile terminal, and transmits and outputs a quality control interface screen and / or an information providing screen in the form of a Hyper-Text Markup Language (HTML) compatible document to the DA terminal 300 through the communication channel, and outputs the same. It is preferable to perform a function of receiving and processing predetermined DA quality control information input (or selected) through the quality management interface screen.

According to another exemplary embodiment of the present invention, when the DA terminal 300 is a CDMA-based wireless terminal, the interface unit 310 may connect to the DA terminal 300 and a WAP (Wireless Application Protocol) and / or ME (Mobile). Connect a predetermined communication channel based on the Explorer protocol, and through the communication channel, a quality management interface screen and / or information providing screen in the form of a WML (Wireless Markup Language) and / or HTML compatible document to the DA terminal 300. It is preferable to perform a function of transmitting and outputting the data, and receiving and processing predetermined DA quality management information corresponding to the quality management interface screen from the DA terminal 300.

According to another exemplary embodiment of the present invention, when the DA terminal 300 is an IEEE 802.16x based wireless terminal, the interface unit 310 is a wireless protocol corresponding to the DA terminal 300 and the IEEE 802.16 standard. Connect a predetermined communication channel based on the transmission, transmit and output a predetermined quality management interface screen and / or information providing screen to the DA terminal 300 through the communication channel, and output the quality from the DA terminal 300. It is preferable to perform a function of receiving and processing predetermined DA quality management information corresponding to the management interface screen.

Referring to FIG. 2, the DA quality control module 305 stores a storage medium storing at least one DA quality management operation information and a predetermined DA quality in the DA terminal 300 in association with the interface unit 310. A UI processing unit 320 for generating (or extracting) a predetermined quality management interface screen for inputting (or selecting) and transmitting management information, and from the DA terminal 300 through the interface unit 310. When DA quality management information transmitted through input (or selection) through the quality management interface screen is received, the quality management policy information corresponding to the DA quality management information is checked from a storage medium provided in the CIO quality management module 205. It is characterized by comprising a DA policy confirmation unit 315 to.

In addition, the DA quality management module 305, a data extraction unit 325 for extracting at least one or more standard data corresponding to the DA quality management information from the quality management management target DBMS 100, and the quality control management And a data structure checking unit 330 for identifying at least one or more conceptual data model information and / or data reference model information corresponding to the DA quality management information from the target DBMS 100.

In addition, the DA quality management module 305, based on the DA quality management operation information stored in the storage medium and the quality management policy information confirmed by the DA policy check unit 315, the database quality shown in Figure 1 According to a data management process on the management framework characterized in that it comprises a data quality management unit 335 for managing at least one or more standard data extracted through the data extraction unit 325.

In addition, the data quality management unit 335 is a database quality management frame shown in FIG. 1 based on the DA quality management operation information stored in the storage medium and the quality management policy information checked by the DA policy checking unit 315. The conceptual data model information and / or data reference model information identified by the data structure checking unit 330 is managed according to a data management process on a work.

According to the exemplary embodiment of the present invention, the DA quality management operation information stored in the storage medium included in the DA quality management module 305 corresponds to the DA quality management information from the quality management management target DBMS 100. It is preferable to include at least one or more information for managing at least one or more standard data is extracted.

The DA quality management operation information may include a standard word dictionary, a standard domain dictionary, a standard term dictionary, a standard code, and a data standard element.

According to the implementation method of the present invention, the standard word dictionary of the DA quality management operation information is a dictionary which defines a word of the minimum unit that is used in a business or an institution and has a certain meaning. Or by convention, using the same word in different meanings (for example, when you transfer assets to "acquisitors", where you give and receive "conciliators" in opposite ways, or in a single word). It is desirable to prevent problems such as using various meanings (eg, "processors").

Here, it is preferable that the management criteria for the standard word dictionary of the DA quality management operation information include standardity, referenceability, generality, representativeness, and the like.

Standardity of the management criteria for the standard word dictionary of the DA quality management operation information, the standard word defined in the standard word dictionary is a word in a dictionary meaning generally used or generally used in the scope of work targeted by the information system. It should be extracted from the middle, including overworking or dialects, and minimizing the use of abbreviations.

In addition, the possibility of reference to the management criteria for the standard word dictionary of the DA quality management operation information includes that the standard word defined in the standard word dictionary can be referred to when defining a new task in the company or institution. It is done by

In addition, the generality of the management criteria for the standard word dictionary of the DA quality management operation information includes that the standard word defined in the standard word dictionary does not differ significantly from the general word so that the general person can understand the meaning of the word. It is done by

In addition, the representativeness of the management criteria for the standard word dictionary of the DA quality management operation information, standard words defined in the standard word dictionary may have synonyms, but words declared as standard words may represent synonyms having similar meanings. To make it possible.

The method for managing the standard word dictionary of the DA quality management operation information includes extracting the standard word based on entities and attributes managed throughout the enterprise as individual units and by using physical names (English name and English abbreviation) based on logical names (Korean names). Name), and similar terms are collectively managed together, and the standard word dictionary is preferably managed so that the structure of words such as synonyms, synonyms, antonyms, and the like is defined together.

According to an embodiment of the present invention, the standard domain dictionary of the DA quality management operation information is a dictionary defining a range of values satisfying a condition defined in an attribute of domain, wherein the standard domain is used throughout the enterprise. It is desirable to group logically and physically similar types of data among the existing data to define the type and length of data belonging to that group.

Here, it is preferable that the management criteria for the standard domain dictionary of the DA quality management operation information include standardity, uniqueness, work orientation, and the like.

The standardization of the management criteria for the standard domain dictionary of the DA quality management operation information includes that the standard domain defined in the standard domain dictionary is defined for attributes that are commonly used at the enterprise level. For example, it is preferable to define and use a standard domain because the account number of the bank does not vary depending on the bank subtask or the financial product.

In addition, the uniqueness of the management criteria for the standard domain dictionary of the DA quality management operation information comprises managing so that duplicate domains of the same contents among the standard domains defined in the standard domain dictionary are not declared under different names. .

In addition, the uniqueness of the management criteria for the standard domain dictionary of the DA quality management operation information includes that each domain defined in the standard domain dictionary is declared and managed so as to sufficiently reflect the characteristics of the business. For example, it is preferable to express the domain of the bank account number using '-' to indicate a proper meaning rather than defining without '-'.

The method for managing the standard domain dictionary of the DA quality management operation information includes extracting, grouping, and declaring a standardized domain among attributes implemented in the same form in the DBMS 100 among all data attributes or representative attributes managed throughout the enterprise. All attributes should be assigned to any domain, but not to multiple assignments to at least one domain. The domain may consist of multiple subdomains (composite domains) or one domain It manages to be used in a duplicated domain, and manages the attribute and domain to be mapped to each other, and recommends selecting and registering a domain of the attribute when a new attribute is added, and deleting a domain Enabled only if no attribute is used It is desirable to manage.

According to an embodiment of the present invention, the standard term dictionary of the DA quality management operation information is a dictionary that defines at least one term that is frequently used in a business and includes at least one term defined by combining standard words. The words are individual, but the terminology can vary depending on the nature of the task and organization. By defining the above standard terminology, it is possible to minimize the problems caused by the lack of understanding or confusion when terminology requires communication between different tasks within an institution or company.

Here, it is preferable that the management criteria for the standard term dictionary of the DA quality management operation information include standardity, generality, work orientation, and the like.

Standardization of the management criteria for the standard term dictionary of the DA quality management operation information may include minimizing enterprise-wide confusion caused by differences in terms used or meanings defined in the standard term dictionary.

In addition, the generality of the management criteria for the standard glossary of the DA quality management operation information is such that the terms defined in the standard glossary should not be overly defined by the business perspective and may not be intuitively understood or cause semantic confusion. It is made to include. In other words, terms used differently from the general meaning should be replaced with other terms.

In addition, the business orientation of the management criteria for the standard term dictionary of the DA quality management operation information, including that the terms defined in the standard term dictionary can be used by using an abbreviation or separately defined internally to reflect the task Is done. However, excessive use of abbreviations or the development of new terms should not undermine their understanding of the work.

In the method for managing the standard term dictionary of the DA quality management operation information, the standard term is managed to generate a combination of the words defined in the standard word dictionary for the terms of the entity and the attribute being used throughout the enterprise. The dictionary is defined and managed by dividing it into entity term dictionary and attribute term dictionary. Each term has logical name (Korean name) and physical name (English name), and it is necessary to include and manage explanation of term range and qualification form. desirable.

According to an exemplary embodiment of the present invention, the standard code of the DA quality management operation information means that the standard code of the DA quality management operation information is replaced with a symbol within a limited range according to a standard defined for shaping various data values. Not only codes that are legally and institutionally assigned to each industry but are commonly used, codes that are defined and used internally by organizations or companies are targeted.

Here, it is preferable that the management criteria for the standard code of the DA quality management operation information include reusability, consistency, uniqueness and information analysis.

The reusability of the management standards for the standard codes of the DA quality management operation information is higher than that of the standard organizations, the government and the public rather than the codes defined by the institution or the company itself in order to improve the understanding of the data and to facilitate the code management. This includes the use of code defined by the organization.

Consistency of the management criteria with respect to the standard code of the DA quality management operation information comprises the code corresponding to the standard code to be used consistently with a single value. For example, 'Y / N' or '1/0', etc. should not be used in combination.

In addition, the uniqueness of the management criteria for the standard code of the DA quality management operation information includes that the code corresponding to the standard code is defined uniquely. If the work code is duplicated, it can cause serious problems of inconsistency with data at the enterprise level.

In addition, the information analysis of the management standard with respect to the standard code of the DA quality management operation information includes the management of all the data in the range possible. In other words, the higher the weight of the value entered by referring to the code than the value directly entered as text, the easier it is to obtain valuable results when analyzing information.

The method for managing the standard code of the DA quality management operation information is to analyze the code used throughout the enterprise and the standardization code of the standardization organization or the government and public institutions to determine whether to use the standardization code, and the code is standardized. Should be managed by the team according to strict standards and should not be created or modified by the user 600 arbitrarily, and the code should be closely related to the domain, but the range of values is clearly defined in the domain. (E.g., whether or not 'is indicated by' Y / N ') is preferably managed so as not to code and manage.

According to an embodiment of the present invention, the data standard element of the DA quality management operation information refers to a standard for data related elements required to design and build a system, and the data related element standard object is a subject of a logical data model. Naming conventions such as realm, entity, attribute relationship names, physical object objects Subject Areas, Relationships, Database & Instances, Indices, Constraints, Sequences, Custom Procedures & Functions, Synonyms, Views, Rollback Segments, Tablespaces, File Names, Script Names, etc. It includes.

The system operation may have a mixture of essential elements necessary only for system operation and elements generated by the system operator. The management criteria for data standard elements of the DA quality management operation information are essential elements for the system operation. It is made, including.

For example, elements that simply load the result of the program execution are necessary for backtracking when problems occur, but are not essential elements of system operation, and selection criteria of the management target among the data related elements are essential elements for system operation. Be able to be the primary target.

The method for managing data standard elements of the DA quality management operation information includes managing to accurately select the elements necessary for operating the system, extracting the elements required for the design and construction of the system, and defining the elements for which standards are required. It is advisable to manage to define business standards for.

According to the exemplary embodiment of the present invention, the DA quality management operation information stored in the storage medium included in the DA quality management module 305 includes conceptual data model management information and / or data reference model management information. It is preferable.

The conceptual data model management information includes a subject area, a core entity, a core relationship, and the like.

According to the method of the present invention, the subject area of the conceptual data model management information means a data set having high business intimacy.

Here, it is preferable that the management criteria for the subject area of the conceptual data model management information include atomicity, concentration, work orientation, and the like.

The atomicity of the management criterion for the subject area of the conceptual data model management information is such that the predetermined unit subject area includes a group of entities that are not affected by an entity or a relationship of another subject area as much as possible.

In addition, the centralization of the management criteria in the subject area of the conceptual data model management information may include causing the relationship with the entities in the unit subject area to be concentrated in the unit subject area.

In addition, the work orientation of the management criteria for the subject area of the conceptual data model management information may include naming the subject area in a singular unit representing business clarity.

In the method for managing the subject area of the conceptual data model management information, a set of entity areas which are more effective to deal with in the same area of business are declared as one subject area, and the subject areas are managed to be divided into several according to the variety of tasks. In addition, although the scope of clearly distinguishing tasks may be defined as one subject area, it is desirable to manage the number of entities shared between different subject areas as much as possible.

According to an embodiment of the present invention, the core entity of the conceptual data model management information is a data set to be managed in the business area, and should have two or more attributes and two or more data instances. It is a homogeneous, independent data set and corresponds to a data unit that exists permanently. Among them, the key entity, the core entity, which is the main entity, is a high-level entity that is the basis of a task and can create a number of child (task, transaction) entities.

Here, it is preferable that the management criteria for the core entity of the conceptual data model management information include aggregation, identification, persistence, usability, relationship, and the like.

Aggregation of management criteria for key entities of the conceptual data model management information comprises such that the entity consists of a set of data having two or more attributes and two or more data instances.

In addition, the identification of the management criteria for the core entity of the conceptual data model management information includes that the entity can uniquely distinguish each data instance of the entity by one or more attributes.

In addition, the persistence of the management criteria for the core entity of the conceptual data model management information is a data set that must exist permanently according to the activity cycle of the task, the data that must disappear or be generated when the contents of the task are changed. Aggregates are inappropriate for declaring and managing as such entities.

In addition, the usability of the management criteria for the core entity of the conceptual data model management information is a data set that must be used within the business scope, and if declared but not used, there is no value as an entity.

In addition, the relationship between the management criteria for the core entity of the conceptual data model management information includes that the entity must have a relationship with another entity, and the entity without a relationship may be an unused entity. Violation of usability.

The method for managing the core entity of the conceptual data model management information, the entity is managed to be collected from a document, a journal, an interview, a related technical book, a DFD, another system, a report, a field survey, and the entity is logical Declare it correctly by dividing it into units, but manage it so that one entity looks semantically different so that it is not duplicated (i.e. if one entity looks different depending on its state, identify the homogeneity of the data and declare it as one entity as a subtype). Should be managed).

According to the implementation method of the present invention, the core relationship of the conceptual data model management information indicates a logical relationship between the core entities, and the business rule that affects the existence form or mutual influence of the entities in the present or near future. It expresses a useful relationship in a limited way, and has a relationship name, an optional specification, and a relationship type. In the relational data model, the relationship must exist between entities.

Here, it is preferable that the management criteria for the core relationship of the conceptual data model management information include selectivity, formability, work orientation, and the like.

The selectivity of the management criteria for the key relationship of the conceptual data model management information includes the relationship being able to distinguish 'required' and 'selection'.

In addition, the form nebula of the management criteria for the core relationship of the conceptual data model management information, the relationship is made to include the definition (degree) of 1: 1, 1: M, N: M to be managed.

In addition, the task orientation of the management criteria for the core relationship of the conceptual data model management information clearly indicates how the relationship between the two entities affects each other (ie, the existence of an instance of a child entity must If the existence of the parent instance is required but the existence of the child instance is not affected, then the relationship may be made to clearly express the effect of the existence between such parent and child entities.

In the method for managing the core relationship of the conceptual data model management information, the core relationship may maintain the M: M relationship as it is in the conceptual data model step and manage the M: M relationship to include the resolved entity. The relationship name between parent and child must be defined to be defined, and the relationship name must be specific, and the relationship between the parent (parent) and the receiver (child) between entities must be clearly defined, and the data having the relationship must exist. It is preferable to manage so that selectivity for the case where there is no target data having a relationship with the case, and manage to be able to clearly express the form of the relationship between the predetermined data and one or more data.

Referring to FIG. 1 according to an embodiment of the present invention, an overview data model may be placed on top of the conceptual data model according to the intention of a person skilled in the art, wherein the overview data model may include a data area and a data set in a work area. Defined from an enterprise-wide perspective, but not limited to, and / or each data region has a relationship with other data regions, and / or more primized attributes that are commonly used in the public interest rather than the interests of an institution or company. It is possible to define at the level of form.

The data reference model management information is a reusable data model. The attribute reference unit, entity, and entire business area unit may also be data reference models. Conceptual data models, logical data models, and physical data models can also be scopes of data reference models.

Here, it is preferable that the management criteria for the data reference model include generality, simplicity, standardity, accuracy, information availability, and classification.

The generality of the management criteria for the data reference model includes information on specific data of a specific task, and defines and manages something that can be referred to in various work areas in general.

In addition, the simplicity of the management criteria for the data reference model includes not limited to a specific task so as to maximize the utility.

In addition, the standard of the management criteria for the data reference model includes the data term being expressed to maximize the reference usability of the data model using terms that can be understood at a common sense and general level.

In addition, the accuracy of the management criteria for the data reference model includes that the information to be managed is accurate only as a model having the nature of reference.

In addition, the information availability of the management criteria for the data reference model includes not only the relationship between the entities, but also the entity and the definition of the entity, the data management rules of the entity, and the attribute definition can be stored and referenced together.

In addition, the classification of the management criteria for the data reference model is made to be classified not only within the work area and industry, but also within each step of the data structure and the scope of the data reference model.

The method for managing the data reference model is preferably defined in a central organ or upper organization and managed to be shared and shared by the lower organ or organization.

The UI processing unit 320 has a functional configuration (eg, DA) provided in the DA terminal 300 when a predetermined DA terminal 300 approaches the DA quality management module 305 through the interface unit 310. A predetermined quality management interface screen for inputting (or selecting) predetermined DA quality management information corresponding to a browser program included in the terminal 300 and transmitting the predetermined quality management interface to the DA quality management module 305 through the network means. The DA terminal 300 generates the quality management interface screen generated and / or extracted from a predetermined DB (not shown) and linked with the interface unit 310 through the network means. It is characterized in that to provide.

Thereafter, the DA terminal 300 inputs (or selects) predetermined DA quality control information based on the quality management interface screen, and inputs the input (or selected) DA quality management information through the network means. Transmit to quality control module 305.

When the DA policy check unit 315 inputs (or selects) predetermined DA quality control information through the quality management interface screen from the DA terminal 300 and is provided through the interface means, the interface unit 310 is provided. And extracting and confirming predetermined quality management policy information corresponding to the DA quality management information from a storage medium provided in the CIO quality management module 205, and corresponding to the DA quality management information. The quality management policy information of the is provided to the data quality management unit 335.

The data extracting unit 325 extracts at least one or more standard data corresponding to the DA quality management information from the quality control management target DBMS 100, wherein the standard data is the DA quality management module ( 305) refers to standard related data defined in common format and contents for terms, domains, codes, and other data related elements used in this standard, and is essential for securing the data quality of the information system. And management to prevent data inconsistencies and data errors and to improve understanding of the data, and to implement data integration efficiently by implementing a single, standardized information system at the institutional or enterprise level. It is characterized by.

The data structure checking unit 330 confirms at least one or more conceptual data model information and / or data reference model information corresponding to the DA quality management information from the quality control management target DBMS 100. The conceptual data model refers to a model that defines a subject area and a core data set of data meeting the business requirements of the DA quality management module 305 and defines a relationship therebetween. The data reference model refers to the database quality management. Standard data set and management by work area and subject area for the purpose of mutual operation of data models used by each organization and reference and reuse of other organizational data models for the construction and maintenance of data architecture of the information system to which the framework is applied The data model that defines the items.

The data quality management unit 335 is configured on the database quality management framework shown in FIG. 1 based on the DA quality management operation information stored in the storage medium and the quality management policy information confirmed by the DA policy checking unit 315. Manage at least one or more standard data extracted through the data extraction unit 325 according to a data management process, and / or confirmed by the DA policy management unit 315 and DA quality management operation information stored in the storage medium. Managing the conceptual data model information and / or data reference model information identified by the data structure checking unit 330 according to a data management process on the database quality management framework shown in FIG. It is characterized in that, for a detailed description thereof through the flow chart shown below The people.

Among the quality control subjects on the database quality management framework, the modeler 400 and the terminal 400 used by the modeler 400 access the modeler quality management module 405 through a predetermined interface means. The quality management module 405 is a communication channel for database quality management for the DBMS 100 based on the database quality management framework shown in FIG. 1 and the modeler 400 via the interface means. It characterized in that it comprises an interface unit 410 for connecting and managing.

According to an embodiment of the present invention, when the modeler 400 terminal 400 is a wired terminal, the interface unit 410 may establish a Hyper-Text Transfer Protocol (HTTP) protocol with the modeler 400 terminal 400. By connecting a predetermined communication channel based on the transmission, and transmits the quality management interface screen and / or information providing screen in the form of HTML (Hyper-Text Markup Language) compatible document to the modeler 400, the terminal 400 through the communication channel It is preferable to perform a function of outputting and receiving and processing predetermined modeler quality management information input (or selected) through the quality management interface screen from the modeler 400 and the terminal 400.

According to another exemplary embodiment of the present invention, when the modeler 400 terminal 400 is a CDMA-based wireless terminal, the interface unit 410 is connected to the modeler 400 terminal 400 and a WAP (Wireless Application Protocol). And / or connect a predetermined communication channel based on a Mobile Explorer (ME) protocol, and the quality of a WML (Wireless Markup Language) and / or HTML compatible document form to the modeler 400 and the terminal 400 through the communication channel. It is preferable to perform a function of transmitting and outputting a management interface screen and / or an information providing screen and receiving and processing predetermined modeler quality management information corresponding to the quality management interface screen from the modeler 400 and the terminal 400. .

According to another exemplary embodiment of the present invention, when the modeler 400 terminal 400 is an IEEE 802.16x based wireless terminal, the interface unit 410 is the modeler 400 terminal 400 and the IEEE 802.16. Connecting a predetermined communication channel based on a wireless protocol corresponding to a standard, transmitting and outputting a predetermined quality management interface screen and / or information providing screen to the modeler 400 and the terminal 400 through the communication channel, The modeler 400 preferably performs a function of receiving and processing predetermined modeler quality management information corresponding to the quality management interface screen from the terminal 400.

Referring to FIG. 2, the modeler quality management module 405 is a storage medium that stores at least one modeler quality management operation information, and is connected to the interface unit 410 in a predetermined manner by the modeler 400 and the terminal 400. The modeler 400 through the UI processing unit 420 and the interface unit 410 to generate (or extract) a predetermined quality management interface screen for inputting (or selecting) and transmitting modeler quality management information of the model. When the modeler quality management information received by inputting (or selecting) transmitted from the terminal 400 through the quality management interface screen is received, the modeler quality management information corresponding to the modeler quality management information from the storage medium included in the CIO quality management module 205 is received. It characterized in that the modeler 400 is provided with a policy check unit 415 for confirming the quality management policy information.

In addition, the modeler quality management module 405, a data extraction unit 425 for extracting at least one or more model data corresponding to the modeler quality management information from the quality management management target DBMS (100), and the quality control management And a data structure checking unit 430 for checking at least one logical data model information corresponding to the modeler quality management information from the target DBMS 100.

In addition, the modeler quality management module 405 is shown in Figure 1 based on the modeler quality management operation information stored in the storage medium and the quality management policy information confirmed by the modeler 400 policy check unit 415. And a data quality management unit 435 for managing at least one model data extracted through the data extraction unit 425 according to a data management process on the database quality management framework.

In addition, the data quality management unit 435 is a database shown in FIG. 1 based on modeler quality management operation information stored in the storage medium and quality management policy information confirmed by the modeler 400 policy checking unit 415. And managing the logical data model information identified by the data structure checking unit 430 according to a data management process on the quality management framework.

According to the exemplary embodiment of the present invention, the modeler quality management operation information stored in the storage medium included in the modeler quality management module 405 corresponds to the modeler quality management information from the quality management management target DBMS 100. It is preferable to include at least one or more information for managing at least one or more model data to be extracted.

Here, the management criteria of the model data through the modeler quality management operation information, it is preferable to include completeness, consistency, traceability, interconnection, freshness and compatibility.

Integrity of the management criteria of the model data includes making the model data include metadata for data structures of all stages such as conceptual data models, logical data models, physical data models, databases.

In addition, the consistency of the management criteria of the model data includes that the model data is defined in compliance with words, terms, domains and data standard elements.

In addition, the traceability of the management criteria of the model data, the model data comprises that it is easy to track the change history of the data model and to meet the utilization requirements for the historical data model.

In addition, the correlation between the management criteria of the model data, the model data comprises to represent the inter-relationship between the data models to manage the data structure in a three-dimensional structure.

In addition, the up-to-dateness of the management criteria of the model data includes making the model data logically match not only the business rules expressed in the step-by-step data model but also the database implemented in the actual system.

In addition, the compatibility of the management criteria of the model data includes that the model data is compatible with the standard data and the management data.

In the method for managing the model data, the data structure and the model data representing the structure should be managed separately, and if the data model is changed, the data model before and after the change is, of course, the affected application and SQL (Structured) It is desirable to manage the history of Query Language together.

According to the exemplary embodiment of the present invention, the modeler quality management operation information stored in the storage medium included in the modeler quality management module 405 preferably includes logical data model management information.

Here, the logical data model management information includes a subject area, an entity, a relationship, an attribute, and the like.

According to an embodiment of the present invention, the subject area of the logical data model management information is to declare and manage a data set having high business intimacy as one subject area.

Here, the management criteria for the subject area of the logical data model management information, the subject area management criteria and method of the logical data model preferably follows the concept data model subject area management criteria.

According to an embodiment of the present invention, the entity of the logical data model management information may include sub-type information including definitions of a conceptual data model and in which history management, homogeneity, and independence information are identified in more detail.

Here, it is preferable that the management criteria for the entity of the logical data model management information include completeness, persistence, identification, homogeneity, normalization, and the like.

The completeness of the management criteria for the entities of the logical data model management information comprises maintaining two or more attributes and two or more instances in the respective data sets.

In addition, the persistence of the management criteria for the entities of the logical data model management information is to include a data set that is currently managed or a data set to be managed in the future.

In addition, the identification of the management criteria for the entity of the logical data model management information comprises the presence of one or more attributes that can individually distinguish instances of the entity.

In addition, the homogeneity of management criteria for the entities of the logical data model management information is such that the entity, which is a predetermined data set, includes a data set in which homogeneous data is collected.

In addition, normalization of the management criteria for the entity of the logical data model management information includes making the entity generally normalize up to the third normalization.

The method for managing the entity of the logical data model management information follows the method for managing the conceptual data model, and it is preferable to add and manage detailed information such as an entity definition and a data generation rule according to the detail of the information.

According to the embodiment of the present invention, the relationship of the logical data model management information includes the definition of the conceptual data model, and means that all M: M relationships are resolved in the detailed logical data model step.

Here, it is preferable that the management criteria for the relationship of the logical data model management information include the selectivity, the relationship type, the relationship name, and the like.

The selectivity of the management criteria for the relationship of the logical data model management information includes making the relationship be divided into mandatory and optional, wherein the mandatory relationship must have an instance with the relationship present in the entity. Means.

In addition, the relationship form of the management criteria for the relationship of the logical data model management information includes that the relationship can have a relationship of 1: 1 or 1: M, M: N.

In addition, the relationship name of the management criterion for the relationship of the logical data model management information may be omitted in the expression when the relationship is clear, but in general, it is necessary to have a relationship name when establishing the relationship between the entities. It is made to include.

In the method of managing the relationship of the logical data model management information, it is preferable to manage to follow the method of managing the conceptual data model, and to define and manage the business rules contained in the relationship in detail.

According to an embodiment of the present invention, the attribute of the logical data model management information means information items to be managed in an entity.

Here, it is preferable that the management criteria for the attributes of the logical data model management information include atomicity, consistency, integrity, informationality, and the like.

The atomicity of the management criteria for the attributes of the logical data model management information should be divided up to a meaningful minimum unit, and one attribute includes information of several states at the same time.

In addition, the consistency of the management criteria for the attributes of the logical data model management information, the predetermined attribute is made to include one data type and manages only one data.

The integrity of the management criteria for the attributes of the logical data model management information includes making the data of the referenced attribute coincide with the data of the attribute referring to the attribute.

The informationality of the management criteria for the attributes of the logical data model management information includes making the level of detailing determined within a meaningful range within the task.

The method of managing attributes of the logical data model management information may include managing the attributes not to be indiscriminately increased according to a request of the user 600 after initially determining the attributes within a management item range of an entity, wherein the attributes are existing information. When it is not possible to extract from, it is desirable to manage the addition so that it can be added and the entity can be added according to the specification of the attribute.

The UI processor 420 is provided to the modeler 400 when the predetermined modeler 400 terminal 400 approaches the modeler quality management module 405 through the interface unit 410. In response to a functional configuration (eg, a browser program provided in the modeler 400 and the terminal 400), input (or select) predetermined modeler quality management information and transmit the predetermined modeler quality management information to the modeler quality management module 405 through the network means. Generate a predetermined quality control interface screen, and / or extract from a predetermined DB (not shown), and link the generated quality control interface screen with the interface unit 410 to the network means. Through the modeler 400, characterized in that provided to the terminal 400.

Thereafter, the modeler 400 terminal 400 inputs (or selects) predetermined modeler quality management information based on the quality management interface screen, and transmits the inputted (or selected) modeler quality management information to the network means. The modeler is transmitted to the quality management module 405 through.

When the modeler 400 policy check unit 415 inputs (or selects) predetermined modeler quality management information from the modeler 400 terminal 400 through the quality management interface screen and is provided through the interface means, And extracting and confirming predetermined quality control policy information corresponding to the modeler quality management information from a storage medium provided in the CIO quality management module 205 in cooperation with the interface unit 410. Predetermined quality management policy information corresponding to management information is provided to the data quality management unit 435.

The data extraction unit 425 extracts at least one or more model data corresponding to the modeler quality management information from the quality management management target DBMS 100, wherein the model data is the database quality management framework. Refers to data required to operate and manage the data model on the information system to which the data is applied, and includes data reference model, conceptual data model, logical data model, metadata about physical data model, and DBMS 100 object information. .

The data structure checking unit 430 confirms at least one or more logical data model information corresponding to the modeler quality management information from the quality management management target DBMS 100, wherein the logical data model is the database. The conceptual data model of the information system to which the quality management framework is applied is a detailed model that defines logical data sets, management items, and relationships.

The data quality management unit 435 is based on the modeler quality management operation information stored in the storage medium and the quality management policy information confirmed by the modeler 400 policy check unit 415, the database quality management shown in Figure 1 Manage at least one or more model data extracted through the data extraction unit 425 according to a data management process on the framework, and / or modeler quality management operation information and the modeler 400 policy checker stored in the storage medium. Managing the logical data model information checked by the data structure checking unit 430 according to a data management process on the database quality management framework shown in FIG. 1 based on the quality management policy information confirmed by 415. It is characterized in that, the detailed description thereof will be described in detail through a flow chart shown below The.

The DBA terminal 500 used by the database manager (DBA) 500 among the quality control subjects on the database quality management framework is characterized in that the DBA quality management module 505 is accessed through a predetermined interface means. The DBA quality management module 505 communicates with the DBA terminal 500 through the interface means for quality control of the database for the DBMS 100 based on the database quality management framework shown in FIG. It characterized in that it comprises an interface unit 510 for connecting and managing.

According to an embodiment of the present invention, when the DBA terminal 500 is a wired terminal, the interface unit 510 has a predetermined communication channel based on the DBA terminal 500 and the Hyper-Text Transfer Protocol (HTTP) protocol. To the DBA terminal 500, and transmits and outputs a quality control interface screen and / or an information providing screen in the form of a Hyper-Text Markup Language (HTML) compatible document to the DBA terminal 500, and outputs the DBA terminal 500. It is preferable to perform a function of receiving and processing predetermined DBA quality management information input (or selected) through the quality management interface screen from the control panel.

According to another exemplary embodiment of the present invention, when the DBA terminal 500 is a CDMA-based wireless terminal, the interface unit 510 may connect to the DBA terminal 500 and a WAP (Wireless Application Protocol) and / or ME (Mobile). Connect a predetermined communication channel based on the Explorer protocol, and through the communication channel, a quality management interface screen and / or an information providing screen in the form of a WML (Wireless Markup Language) and / or HTML compatible document to the DBA terminal 500. It is preferable to perform a function of transmitting and outputting the data, and receiving and processing predetermined DBA quality management information corresponding to the quality management interface screen from the DBA terminal 500.

According to another embodiment of the present invention, when the DBA terminal 500 is an IEEE 802.16x based wireless terminal, the interface unit 510 may be a wireless protocol corresponding to the DBA terminal 500 and the IEEE 802.16 standard. Connect a predetermined communication channel based on the transmission, transmit and output a predetermined quality management interface screen and / or information providing screen to the DBA terminal 500 through the communication channel, and outputs the quality from the DBA terminal 500. It is preferable to perform a function of receiving and processing predetermined DBA quality management information corresponding to the management interface screen.

Referring to FIG. 2, the DBA quality management module 505 stores a storage medium storing at least one DBA quality management operation information, and a predetermined DBA quality in the DBA terminal 500 in cooperation with the interface unit 510. A UI processing unit 520 for generating (or extracting) a predetermined quality management interface screen for inputting (or selecting) and transmitting management information, and the DBA terminal 500 from the DBA terminal 500 through the interface unit 510. When DBA quality management information transmitted through input (or selection) is received through the quality management interface screen, the quality management policy information corresponding to the DBA quality management information is checked from the storage medium provided in the CIO quality management module 205. It is characterized by comprising a DBA policy confirmation unit 520 to.

In addition, the DBA quality management module 505, a data extraction unit 525 for extracting at least one or more management data corresponding to the DBA quality management information from the quality management management target DBMS (100), and the quality control management And a data structure checking unit 530 for checking at least one physical data model information and / or database information corresponding to the DBA quality management information from the target DBMS 100.

In addition, the DBA quality management module 505, based on the DBA quality management operation information stored in the storage medium and the quality management policy information confirmed by the DBA policy check unit 520, the database quality shown in Figure 1 And a data quality management unit 535 for managing at least one or more management data extracted through the data extraction unit 525 according to a data management process on a management framework.

In addition, the data quality management unit 535 based on the DBA quality management operation information stored in the storage medium and the quality management policy information confirmed by the DBA policy check unit 520, the database quality management frame shown in Figure 1 The physical data model information and / or database information identified by the data structure checking unit 530 may be managed according to a data management process on a work.

According to the exemplary embodiment of the present invention, the DBA quality management operation information stored in the storage medium provided in the DBA quality management module 505 corresponds to the DBA quality management information from the quality control management target DBMS 100. It is preferable to include at least one or more information for managing at least one or more management data extracted.

Here, the DBA quality management operation information is characterized in that it comprises use management data, failure and security management data, performance management data, flow management data and quality management data.

According to the exemplary embodiment of the present invention, the use management data of the DBA quality management operation information means data to be managed in order to maximize the utilization value of the database and the satisfaction of the user 600.

Here, it is preferable that the management criteria for the use management data of the DBA quality management operation information include data utilization, user 600 satisfaction, and adequacy of a problem solving time.

The data utilization of the management criteria for the use management data of the DBA quality management operation information includes periodically identifying the data use trend and analyzing and managing the result trend.

In addition, the satisfaction of the user 600 of the management criteria for the use management data of the DBA quality management operation information includes regularly grasping the satisfaction of the user 600 of the database and analyzing and managing the result trend.

In addition, the appropriateness of the time required for solving the problem of the management criteria for the use management data of the DBA quality management operation information, by checking the time required from the occurrence of the problem and the time required to solve the problem after checking the problem, Periods include analysis and management to gauge how systematic and specific the data is being managed.

The method for managing the use management data of the DBA quality management operation information is to collect the data change status by daily, weekly, and monthly, to analyze the time when the sudden change occurs and to establish the causes and trends, anticipated problems and countermeasures. It manages to analyze problems of database use and improvement requirements on a regular basis, manages to define various paths to check problems related to the use of the database, classifies the causes of the problem by type It manages to record in detail the details of the work being processed and the results (problem definition, related databases, personnel and stakeholders, work progress, etc.).

According to the implementation method of the present invention, the failure and security management data of the DBA quality management operation information, to prevent in advance the event that prevents the normal state or effective use of the database, or to be able to quickly recover in case of occurrence Means data to be managed.

Here, the management criteria for the failure of the DBA quality management operation information and security management data, it is preferable to include a periodic status record, recovery procedures and rules and access control.

Periodic status recording of the management criteria for the disturbance and security management data of the DBA quality management operation information is made to manage the backup cycle, backup method, and records related to the storage and recovery of the backup data of the database.

In addition, the recovery procedures and rules of the management criteria for the disturbance and security management data of the DBA quality management operation information is made to define and manage the data recovery procedures and rules applied in case of emergency.

In addition, the access control of the management criteria for the failure of the DBA quality management operation information and the security management data, block access to the database from the inappropriate user 600 inside and outside the database and the authority of the user 600 and This includes managing the grade.

The DBA quality management operation information and the method of managing the security management data management, to evaluate the database to determine the importance, to manage to classify the data to be backed up daily, weekly, monthly according to the importance, The storage location of the backup data is managed to separate the network and server from other systems, and to set up safety devices, establish security regulations for the database, periodically train and promote it, and access the user 600 for each database. Specify authority and manage to check and take measures for illegal access periodically.

According to the exemplary embodiment of the present invention, the performance management data of the DBA quality management operation information means data to be managed essentially to improve the performance of the database.

Here, it is preferable that the management criteria for the performance management data of the DBA quality management operation information include a performance improvement procedure and a performance check cycle.

The performance improvement procedure of the management criteria for the performance management data of the DBA quality management operation information includes defining and managing procedures and rules for improving the performance of the database in order to systematically manage the performance of the database.

In addition, the performance check cycle of the management criteria for the performance management data of the DBA quality management operation information includes that the performance measurement criteria and measurement cycles of the database are defined so as to periodically check the performance of the database.

The method for managing performance management data of the DBA quality management operation information defines a performance measurement standard for the database, manages all the standards to be quantified, measures performance by day, week, and month, and analyzes the trend. To maintain the procedures and rules (eg, query optimization, database structure change, etc.) for improving the performance, and to define the timing and method of the reorganization work according to the database management. In addition, it is preferable to manage to define a rule for when to replace and expand the storage of the database.

According to an embodiment of the present invention, the flow management data of the DBA quality management operation information means data for managing mapping information between source data and target data used when moving predetermined information system data to another information system.

Here, it is preferable that the management criteria for the flow management data of the DBA quality management operation information include a mapping rule of source and target data, a source and target data refinement rule, and the like.

And a mapping rule of source and target data of management criteria for flow management data of the DBA quality management operation information, defining all sources and targets requiring data movement, and defining mapping rules between source targets.

In addition, the source and target data refining rule of the management standard for the flow management data of the DBA quality management operation information, the cleansing rule for the data that complies with the defined source and target mapping rules and violates the definition It is made to include.

The method for managing flow management data of the DBA quality management operation information includes creating a mapping list between the source data and the target data for the database, and managing to confirm that all the source data required by the target system are included. It is managed to check whether the source and the target which do not need the data movement are mapped, and is managed to check whether the deleted source is used as the mapping source, and check whether the data structure of the source and the target is the same. If it is not the same, it is desirable to manage to apply the conversion rule, to check that the conversion rule conforms to the data integrity rules, and to check whether the result ensures data integrity.

According to an embodiment of the present invention, the quality management data of the DBA quality management operation information means data to be basically managed in order to secure the consistency of the data and to perform operations for maintaining and improving data quality. By managing the quality management data, it is possible to prevent inefficient use of data and to prevent data quality degradation due to inconsistency of data that may occur during operation of the data, thereby maintaining high quality data of the entire operating system.

Here, the management criteria for the quality management data of the DBA quality management operation information, it is preferable to include a quality standard, quality inspection cycle, quality verification procedures and rules, and quality improvement procedures.

The quality standard of the management standard for the quality management data of the DBA quality management operation information defines the quality standard of the data managed by the system. Quality standards include the management of ratings based on the importance of the data.

In addition, the quality check cycle of the management criteria for the quality management data of the DBA quality management operation information, to set the measurement cycle for the database performance and data quality, etc. to continuously and regularly perform the data quality management. The quality check period includes making the decision reflecting the required level of the user 600.

In addition, the quality verification procedure and rules of the management criteria for the quality management data of the DBA quality management operation information define data quality verification procedures and rules for applying the defined quality criteria. This includes ensuring that actions taken against exceptions that do not follow the defined procedures and rules are also considered.

In addition, the quality improvement procedure of the management criteria for the quality management data of the DBA quality management operation information, to reflect the measured quality evaluation results to improve the quality of the data and to define a procedure and method for maintaining high quality data It is made to include.

The method for managing quality control data of the DBA quality management operation information includes items requiring data quality management for the database (e.g., entity integrity, referential integrity, domain integrity, attribute, column business rule application, entity, table definition). Data creation, change, deletion rules, triggers, etc., to manage the operation of user-defined DBMS 100 objects, and when data replication is allowed, to derive the consistency between the original data and the replication data, etc. It is advisable to manage to define error correction rules for inappropriate data that fall outside the scope of

According to the exemplary embodiment of the present invention, the DBA quality management operation information stored in the storage medium included in the DBA quality management module 505 may include physical data model management information and / or database management information. Do.

The physical data model management information includes a subject area, a table, a relationship, a column, and the like.

According to an embodiment of the present invention, the management criteria for the subject area of the physical data model management information may be one subject area defined in the logical data model is distributed to different schemas or servers in the physical data model. In some cases, a physical subject area may be managed according to a naming convention of a table in one schema of one server. The subject area management criterion of the physical data model preferably conforms to the criteria of the conceptual data model and the logical data model. The method of managing the subject area of the logical data model management object may include the logical subject area and the instance of the DBMS 100. And managing the correspondence with the schema.

According to an embodiment of the present invention, the table of physical data model management information is divided into one or more physical tables according to one table or subtype or business characteristic according to the physical characteristics of the data and the characteristics of the DBMS 100. Can be.

Here, it is preferable that the management criteria for the table of the physical data model management information include permanence and identification.

The persistence of the management criteria for the tables of the physical data model management information includes data that is currently managed by the data in the tables and needs to be managed in the future.

In addition, the identification of the management criteria for the table of physical data model management information includes making the records in the table distinguishable by one or more column data.

In the method of managing the table of physical data model management information, it is preferable to manage design information such as the life cycle of the data stored in the table and the amount of data to be maintained and managed for a certain period of time.

According to an embodiment of the present invention, the relationship between the physical data model management information means a rule for generating, deleting, and changing data between a parent table and a child table.

Here, it is preferable that the management criteria for the relationship of the physical data model management information include a creation rule, a change rule, a delete rule, and the like.

The generation rule of the management criterion for the relationship of the physical data model management information includes that the data referred to the parent table must exist when generating the data of the child table.

In addition, the rule of changing the management criteria for the relationship between the physical data model management information is that if the key data of the parent table is changed, the reference data of the referenced child table is also changed or if the child data exists, the key data of the parent table is present. This includes preventing the change.

The deletion rule of the management criteria for the relationship between the physical data model management information is that when the parent table data is deleted, the data of the child table referencing the data is deleted together, or the data of the parent table is deleted when the child data exists. It may not be possible.

In the method for managing the relationship of the physical data model management information, since the relationship is a business rule, the management is performed to determine whether to manage at the DBMS (100) level or at the application level first, and the automatic change by the trigger is performed by the DBMS. (100) Since it is difficult to track in case of error, it is desirable to manage it to minimize it as much as possible.

According to the exemplary embodiment of the present invention, the column of the physical data model management information means that the data reflecting the business rule is stored in the standardized domain.

In the method of managing columns of the physical data model management information, predetermined column data is managed to have the same data type and data representation, and the physical attributes of columns having similar data types and representations are defined and managed as domains. It is desirable to.

The database management information includes storage space, tables, constraints, indexes, triggers, DB links, procedures, views, synonyms, and roles.

According to an embodiment of the present invention, the storage space of the database management information means a region (tablespace, data file) defining a table and an index requiring a space for storing data in the database, All data is divided into tables and indexes, and data management begins with the management of storage space.

Here, it is preferable that the management criteria for the storage space of the database management information include safety, security, scalability, and performance guarantee.

Safety of the management criteria for the storage space of the database management information includes that the disk area of the system for the storage space must be secured separately from other program execution areas of the system, and for this purpose, a normal work system Since the DBMS 100 operates a dedicated server, and / or the storage space is a real space in which the data is physically stored, the existence of the storage space is protected from an external threat or disaster.

In addition, the security of the management criteria for the storage space of the database management information, so that the storage space is a real space where the data is physically stored so that the access control to the unauthorized program or user 600 is completely made.

In addition, the scalability of the management criteria for the storage space of the database management information includes the expansion of the storage space and the allocation of the physical disk area is sufficient because the data is continuously increased in the storage space.

In addition, the performance guarantee of the management criteria for the storage space of the database management information, since the large amount of data is called and stored from time to time during the operation of the DBMS 100, the physical disk allocated storage space is a product that can maintain fast performance Appropriate structural arrangements are made.

In the method for managing the storage space of the database management information, the DBA checks the storage space of the system from time to time in consideration of performance and security in accordance with management standards, and manages the final security and safety of the data for the first purpose, and also the developer In addition, it is desirable to control the data to be expanded indiscriminately according to the convenience of the user 600 and to manage the backup to the appropriate level of storage space.

According to an embodiment of the present invention, in the database management information table, entities and attributes are defined as tables in the database, and various methods such as clusters and partitions may be applied according to characteristics of the data, and the data may be increased. Depending on the trend, physical properties may change.

Here, it is preferable that the management criteria for the table of the database management information include periodicity, diversity, security, logic, and the like.

The periodicity of the management criteria for the table of the database management information includes the data in the table being backed up at regular intervals or regenerated for performance.

In addition, the variety of management criteria for the table of the database management information, the data in the table according to the appropriate distribution strategy and table storage space definition method for performance, Partition (Partition), Cluster (Cluster), Index Organized Table (IOT) , Etc., to be defined in several forms.

In addition, the security of the management criteria for the table of the database management information, so that the table access, creation, modification, deletion rules are defined in a table unit, column unit to the user 600 of a limited range according to the authority and use It is made to include.

In addition, the logicality of the management criteria for the table of the database management information includes that the addition of the table and the addition of the column must be performed by referring to a logical data model, which is not based on the logical data model. The addition of tables and columns on the DBMS 100 will yield indiscriminately redundant data, resulting in poor data quality.

The method of managing the table of the database management information is appropriate so that the DBA manages the data of the table in consideration of performance and security according to the management criteria, and does not indiscriminately create the table in consideration of the convenience of the developer or the user 600. Management is preferably limited.

According to an embodiment of the present invention, constraints of the database management information may include business such as Not Null, Default, Foreign Key Constraint, and Check condition in the database. It is recommended that the rule be defined in the column, but the constraint on applying the relationship between tables means that the rule is applied in parallel with the application.

Herein, the management criteria for the constraints of the database management information may include a not null condition, a default, a foreign key condition, a check condition, and the like in the database. desirable.

The not null condition of the management criterion for the constraint of the database management information includes defining a column in which data must exist in the table.

The default condition of the management criterion for the constraint of the database management information may include defining basic data when it is impossible to define a final value in a column in which the data must exist.

The foreign key condition of the management criteria for the constraint of the database management information includes defining and managing a rule for inputting, deleting, and generating a relationship defined in the physical data model.

In addition, the check condition of the management criterion for the constraint of the database management information includes defining such that only data within a predefined type or range exists in a specific column.

In the method of managing the constraints of the database management information, the reflection of the constraints on the column is managed to be consistent with the attribute definition of the logical data model, and the rule on the relationship is managed to be maintained by the application. desirable.

According to the method of the present invention, the index of the database management information is not reflected in the logical data model in the database, but is one of the data stores for speeding up data access, and manages the index of the database management information. Criteria can be defined in various ways according to business requirements. However, the higher the redundancy of the columns, the more wasteful of storage space and adversely affects the speed of data entry, deletion, and update. Various kinds may exist according to the kind of 100).

The index management method of the database management information is generally maintained in the form of B + Tree. In this case, since the index has little reuse of storage space, it is preferable to regenerate the index periodically.

According to an embodiment of the present invention, the trigger of the database management information, in connection with a table in the database to perform a predefined function, the management criteria for the trigger of the database management information, BEFORE upon creation of the trigger The key can be used to specify that the Tuple (row, record) can be started before an event occurs. On the contrary, the AFTER key can be used to activate it after the event is completed.

In the method of managing the trigger of the database management information, another trigger may be sequentially activated when the trigger is executed. Therefore, the creation and use of triggers must be carefully defined and unwanted results can be obtained by the use of invalid triggers, and one or more triggers can be defined that specify the same event in the same table, but this does not change the triggering sequence of the triggers. Unpredictable and may be omitted by those skilled in the art.

According to an embodiment of the present invention, the DB link of the database management information is to connect a database remote from the database to process data in another server in one server in one SQL statement, The management criteria for DB link of database management information is defined in a distributed server environment when you want to easily call data of tables located in one server to another server or another database instance.

In the method of managing the DB link of the database management information, since the DB link is properly created but the connection often occurs at the time of querying, it is necessary to verify the operation in actual use, and also the abuse of the DB link. Can slow down the execution of SQL, so it is desirable to properly manage it in consideration of the performance of the information system.

According to an embodiment of the present invention, the procedure of the database management information, the function (Function) and the procedure (Procedure) in the database is defined and used by the user 600, the function and the procedure is written in the program SQL statement The function and procedure can be called by using SQL statement.

The management criterion for the procedure of the database management information is that the data of the table is inputted, modified, or deleted by SQL statements, but when performing complex tasks or when the same type of SQL is repeated, This includes defining a procedure.

The method of managing the procedure of the database management information is that the function and the procedure are managed to increase the reuse rate of the function and the procedure defined in another schema by declaring synonyms when the commonity is more emphasized, and the SQL used incorrectly in the function or the procedure. Because the statement can greatly slow down the overall execution speed, it is desirable to manage the statement through performance verification.

According to an embodiment of the present invention, the view of the database management information is an object created to view data in the database, and does not require a physical storage space, and the execution result of the SQL statement defined by the user 600 is displayed. As the virtual data area shown, there may also be a view having actual physical storage space according to the type of commercial RDBMS 100.

The management criteria for the view of the database management information include creating access for important data, reducing database complexity, hiding complex database designs, and simplifying tasks including distributed queries on heterogeneous data.

In the method of managing the view of the database management information, the complex view may not grasp the intention of the user 600 properly, it may be difficult to grasp the work of the SQL performed as a whole, and may also affect the speed. It is advisable to manage the use and the use of views that are too complex.

According to an embodiment of the present invention, the synonym of the database management information means an alias for a table in the database, a general synonym can be created by all users, and ownership can be used only by the creator. As a synonym for PUBLIC, only DBAs can create and delete.

The management criterion for synonyms of the database management information includes defining synonyms for table data defined in another schema when the subject area is defined as a schema, but which must be frequently referred to frequently in business.

In the method of managing the synonym of the database management information, the synonym may be generated when one object is to be used in common in multiple schemas, and access to the object may be performed even if the object created in the other schema has read permission. When it is cumbersome, it is better to use synonyms to simplify management.

According to an embodiment of the present invention, the role of the database management information means a rule for creating, deleting, reading and changing the database object, and the authority to grant and control the role is DBA. Has

The management criterion for the role of the database management information is that the ease of use is important when managing the database objects, but also the security and management of the data in the table is important, and the user 600 who uses the database by creating a permission group is important. Properly suggesting permissions involves protecting roles in database objects and defining roles to protect data within objects.

The method of managing the role of the database management information, a combination of high-priority rights that can be frequently used in the commercial RDBMS (100) provides a few basic roles, the role basically provided by the commercial RDBMS (100) It is desirable to manage the system to define and use it according to the security rules in the system.

When the predetermined DBA terminal 500 approaches the DBA quality management module 505 through the interface unit 510, the UI processing unit 520 includes a functional configuration (eg, DBA) provided in the DBA terminal 500. A predetermined quality management interface screen for inputting (or selecting) predetermined DBA quality management information corresponding to a browser program provided in the terminal 500 and transmitting the predetermined quality management interface to the DBA quality management module 505 through the network means. The DBA terminal 500 generates, and / or extracts from a predetermined DB (not shown) and the quality management interface screen generated (or extracted) in conjunction with the interface unit 510 through the network means. It is characterized in that to provide.

Thereafter, the DBA terminal 500 inputs (or selects) predetermined DBA quality management information based on the quality management interface screen, and inputs the input (or selected) DBA quality management information through the network means. Transmission to the quality management module 505.

The DBA policy checking unit 520 inputs (or selects) predetermined DBA quality management information through the quality management interface screen in the DBA terminal 500 and is provided through the interface means. And extracting and confirming predetermined quality management policy information corresponding to the DBA quality management information from a storage medium provided in the CIO quality management module 205, in conjunction with the predetermined information corresponding to the DBA quality management information. The quality management policy information of the is provided to the data quality management unit 535.

The data extraction unit 525 extracts at least one or more management data corresponding to the DBA quality management information from the quality management management target DBMS 100, wherein the management data is the database DBA quality management module. Means standard related data defined in common format and contents for terms, domains, codes, and other data related elements used in (505), and is an essential element to secure data quality of the information system. By defining and managing the system, it is possible to prevent data inconsistency and data errors and to improve the understanding of the data.In addition, it is possible to implement data integration efficiently by implementing a single and standardized information system at the institutional or enterprise level. It is characterized by that.

The data structure checking unit 530 confirms at least one or more physical data model information and / or database information corresponding to the DBA quality management information from the quality control management target DBMS 100, wherein the physical data The model refers to a model in which a physical data model is embodied in consideration of the characteristics and performance of the DBMS 100 of the information system to which the database quality management framework is applied, and the database is applied to the database quality management framework. It is the result of implementing the physical data model of the information system, and it means the data storage where the actual data constructed is stored.

The data quality management unit 535 is configured on the database quality management framework shown in FIG. 1 based on the DBA quality management operation information stored in the storage medium and the quality management policy information confirmed by the DBA policy checking unit 520. Manage at least one or more management data extracted through the data extraction unit 525 according to a data management process, and / or confirmed by the DBA quality management operation information and DBA policy check unit 520 stored in the storage medium. Managing physical data model information and / or database information identified by the data structure checking unit 530 according to a data management process on the database quality management framework shown in FIG. The detailed description thereof will be described in detail with reference to the following flowchart. Order.

Among the quality control subjects on the database quality management framework, the user 600 used by the user 600 accesses the user quality control module 605 through a predetermined interface means. Quality management module 605 is a communication channel for database quality management for the DBMS 100 based on the database quality management framework shown in Figure 1 and the user 600 terminal 600 through the interface means It characterized in that it comprises an interface unit 610 for connecting and managing.

According to an embodiment of the present invention, when the user 600 terminal 600 is a wired terminal, the interface unit 610 may establish a Hyper-Text Transfer Protocol (HTTP) protocol with the user 600 terminal 600. By connecting a predetermined communication channel based on the transmission channel, and transmits the quality management interface screen and / or information providing screen in the form of a Hyper-Text Markup Language (HTML) compatible document to the user 600, the terminal 600 through the communication channel It is preferable to perform a function for outputting and receiving and processing predetermined user quality management information input (or selected) through the quality management interface screen from the user 600 and the terminal 600.

According to another exemplary embodiment of the present disclosure, when the user 600 terminal 600 is a CDMA-based wireless terminal, the interface unit 610 may connect to the user 600 terminal 600 and a WAP (Wireless Application Protocol). And / or connect a predetermined communication channel based on a mobile explorer (ME) protocol, and the quality of a WML (Wireless Markup Language) and / or HTML compatible document form to the user 600 terminal 600 through the communication channel. It is preferable to perform a function of transmitting and outputting a management interface screen and / or an information providing screen and receiving and processing predetermined user quality management information corresponding to the quality management interface screen from the user 600 and the terminal 600. .

According to another exemplary embodiment of the present invention, when the user 600 terminal 600 is an IEEE 802.16x based wireless terminal, the interface unit 610 may be connected to the user 600 terminal 600 and the IEEE 802.16. Connecting a predetermined communication channel based on a wireless protocol corresponding to a standard, transmitting and outputting a predetermined quality management interface screen and / or information providing screen to the user 600 terminal 600 through the communication channel, Preferably, the user 600 performs a function of receiving and processing predetermined user quality management information corresponding to the quality management interface screen from the terminal 600.

Referring to FIG. 2, the user quality management module 605 may be configured to store at least one user quality management operation information in a storage medium and the interface unit 610 in the user 600 terminal 600. The user 600 through the UI processor 620 and the interface unit 610 to generate (or extract) a predetermined QC interface screen for inputting (or selecting) and transmitting user quality control information of the user. When the user quality management information input (or selected) transmitted from the terminal 600 through the quality management interface screen is received, the user quality management information corresponding to the user quality management information from the storage medium included in the CIO quality management module 205 is received. Characterized in that it comprises a user 600 policy check unit 615 to check the quality management policy information.

In addition, the user quality management module 605, a data extraction unit 625 for extracting at least one or more business data corresponding to the user quality management information from the quality management management target DBMS 100, and the quality control management And a data structure checking unit 635 for checking at least one user view information corresponding to the user quality management information from the target DBMS 100.

In addition, the user quality management module 605 is shown in FIG. 1 based on the user quality management operation information stored in the storage medium and the quality management policy information checked by the user 600 policy checking unit 615. According to a data management process on the database quality management framework, characterized in that it comprises a data quality management unit 635 for managing at least one or more business data extracted through the data extraction unit 625.

In addition, the data quality management unit 635 based on the user quality management operation information stored in the storage medium and the quality management policy information confirmed by the user 600 policy check unit 615, the database shown in Figure 1 The user view information identified by the data structure checking unit 635 is managed according to a data management process on a quality management framework.

According to the exemplary embodiment of the present invention, the user quality management operation information stored in the storage medium provided in the user quality management module 605 means data necessary for performing the work and business of an institution or an enterprise. As a result, data can be classified into source, operation, and analysis data.

Here, the user quality management operation information is characterized in that it comprises a source (source) data, operational data (operational) data, and analysis (analysis) data.

According to an embodiment of the present invention, the source data of the user quality management operation information is real world data that is a source of the operation data, and the source data includes a general document, a data source file stored in a PC, an email and a fax. Etc. are included.

Here, it is preferable that the management criteria for the source data of the user quality management operation information include security of source data, safety of source data, and reliability of source data.

The security of the source data of the management criteria for the source data of the user quality management operation information, there is a risk that the source data is not managed systematically by the system, program, or database object and exposed to the unauthorized user 600 There are many important source data, which include paying special attention to security.

In addition, the safety of the source data of the management criteria for the source data of the user quality management operation information, the source data has a high data loss rate in the event of a disaster, it is very difficult to recover the lost source data in case of important source data of safety management This includes keeping the level high.

In addition, the reliability of the source data of the management criteria for the source data of the user quality management operation information is made to include defining the basis for this to determine the accuracy and reliability of the source data.

In the method of managing the source data of the user quality management operation information, the source data is managed by the individual or group owner of the source business data rather than by the integrated system, the retrieval of the source data is generally stored in the system It may take more time than searching, so manage to clearly define the management system, and classify the source data necessary to build the database and manage to define the access authority and creation, change, and destruction rules for each source data. desirable.

According to the implementation method of the present invention, the operational data of the user quality management operation information means data that is stored and managed in a database for use in achieving a goal or a business of an enterprise or an institution, and for simple input / output operation processing Temporary data that is temporarily needed is excluded.

Here, it is preferable that the management criteria for the operation data of the user quality management operation information include accuracy, consistency, up-to-dateness, completeness, ease of use, and ease of search.

The accuracy of the management criteria for the operation data of the user quality management operation information includes storing and managing the same data as the source data existing in the real world.

In addition, the consistency of the management criteria for the operational data of the user quality management operation information includes the data to match the term definition, regulation, standard, attribute definition, data format and the like.

In addition, the latest of the management criteria for the operational data of the user quality management operation information is made, including that the provided data is updated with the most recent content, the latest in the data to maintain the latest of the data You can put a rating (very important, important, or moderate).

In addition, the completeness of the management criteria for the operational data of the user quality management operation information comprises that the data stored in the information system is provided in a complete form without missing items.

In addition, the ease of use of the management criteria for the operation data of the user quality management operation information, so that the interface, help, customer support functions, etc. provided by the information system is provided so that the user 600 is not inconvenient to use the database It is made to include.

In addition, the ease of search of the management criteria for the operation data of the user quality management operation information, so that the search results and output methods according to the search function and the search conditions to be accurate and appropriate so that the desired data can be extracted and utilized in the information system It is made to include.

The method for managing operational data of the user quality management operation information periodically checks and manages data according to defined management criteria and management methods to ensure the accuracy, consistency, freshness and completeness of the data, and uses the data. It is desirable to manage the ease and retrieval of the performance management data in accordance with the management standards and management methods.

According to an exemplary embodiment of the present invention, the analysis data of the user quality management operation information refers to data generated through a process of extracting, transforming, and loading operational data, and analyzing the data. Data must be up-to-date and accurate in order to be able to quickly support the work or activities of the organization or organization.

Here, the management criteria for the analysis data of the user quality management operation information, it is preferable to include the analysis cycle, deadline, summary level, subject orientation, integration, time series, and non-volatile.

An analysis cycle of the management criteria for the analysis data of the user quality management operation information includes determining an analysis and conversion cycle of the operation data which is a source of the analysis data.

In addition, the deadline of the management criteria for the analysis data of the user quality management operation information includes defining a specific time point of the operation data used to convert the operation data into the analysis data.

The summary level of the management criteria for the analysis data of the user quality management operation information defines the summary level required for the analysis data. The level of summarization involves taking into account the scope and depth of operational data.

The subject orientation of the management criteria for the analysis data of the user quality management operation information may include classifying the distributed and managed operational data into a unitary subject area.

In addition, the integration of the management criteria for the analysis data of the user quality management operation information, including allowing the analysis data to be classified according to the same and consistent standards ('male / female', '1/0') Is done.

In addition, the time series of the management criteria for the analysis data of the user quality management operation information is made to include defining the data accumulated for a certain time for various time points.

In addition, the non-volatility of the management criteria for the analysis data of the user quality management operation information includes that the deletion and update of the data does not occur frequently.

The method for managing the analysis data of the user quality management operation information, manages to define a rule for extracting, converting, and loading the operation data into the analysis data, wherein the analysis period, deadline, summary level, etc. It is advisable to manage by defining the size, characteristics, purpose of use, etc.

According to the exemplary embodiment of the present invention, the user quality management operation information stored in the storage medium provided in the user quality management module 605 may include user view management information.

The user view management information may include a screen, an output, and the like.

According to the exemplary embodiment of the present invention, the screen of the user view management information is an interface for providing a final product generated by the information system, and includes an end user screen and a screen for a system administrator.

Here, it is preferable that the management criteria for the storage space of the user view management information include convenience, searchability, system performance, and supportability.

Convenience of the management criteria for the storage space of the user view management information is made to include all the work procedures processed through the user 600 screen to be intuitive and convenient.

In addition, the searchability of the management criteria for the storage space of the user view management information includes the user 600 to quickly and accurately search for the desired information through the screen.

In addition, the system performance of the management criteria for the storage space of the user view management information is made to ensure that all operations processed through the screen to maintain a proper speed and performance (eg, response within 3 seconds).

In addition, the supportability of the management criteria for the storage space of the user view management information may include allowing the user 600 to use appropriate help as necessary during job processing.

In the method of managing the screen of the user view management information, it is preferable to manage not only information on the use and constraints of the screen, but also user requirements and help on the screen.

According to an embodiment of the present invention, the output of the user view management information refers to the output generated through the information system, and includes outputs such as reports, documents, slips, and the like as well as an application program for generating the output. . In general, the output is provided to the end user 600 or used for analysis in the information system.

Here, the management criteria for the storage space of the user view management information is an important data storage tool that can store the value of the data in preparation for the damage of the digital data or the paper output because the recovery rate is very low in case of an accident Since the management can take a lot of cost and manpower, it is preferable to manage the output of the image in parallel to the management of the paper state as the important information management.

In the method for managing the output of the user view management information, since most of the output is provided through the user 600 screen, managing the screen replaces quality management of the output. However, if there is no user 600 screen, it is preferable to manage the work related to the output generation and the output (for example, the scanned output) through the system management tool.

The UI processor 620 is provided to the user 600 terminal 600 when a predetermined user 600 terminal 600 approaches the user quality control module 605 through the interface unit 610. In response to the functional configuration (eg, a browser program provided in the user 600 and the terminal 600), input (or select) predetermined user quality management information and transmit the predetermined user quality management information to the user quality management module 605 through the network means. Generate a predetermined quality management interface screen, and / or extract from a predetermined DB (not shown), and link the generated quality management interface screen with the interface unit 610 to generate the quality management interface screen. Through the user 600 is characterized in that it is provided to the terminal 600.

Thereafter, the user 600 terminal 600 inputs (or selects) predetermined user quality management information based on the quality management interface screen, and transmits the inputted (or selected) user quality management information to the network means. It transmits to the user quality management module 605 through.

When the user 600 policy check unit 615 inputs (or selects) predetermined user quality management information from the user 600 terminal 600 through the quality management interface screen and is provided through the interface means, And extracting and confirming predetermined quality control policy information corresponding to the user quality management information from a storage medium provided in the CIO quality management module 205 in cooperation with the interface unit 610. Predetermined quality management policy information corresponding to management information is provided to the data quality management unit 635.

The data extracting unit 625 extracts at least one or more work data corresponding to the user quality management information from the quality control management target DBMS 100, wherein the work data includes the work of an institution or an enterprise and It refers to the data needed to conduct business. Generally, it can be divided into source, operation, and analysis data according to the data flow.

The data structure confirmation unit 635 confirms at least one or more user view information corresponding to the user quality management information from the quality management management target DBMS 100, wherein the user view, the database quality management The conceptual data model of the information system to which the framework is applied is a detailed model that defines logical data sets, management items, and relationships.

The data quality management unit 635 based on the user quality management operation information stored in the storage medium and the quality management policy information confirmed by the user 600 policy check unit 615, the database quality management shown in Figure 1 Manage at least one or more business data extracted through the data extraction unit 625 according to the data management process on the framework, and / or user quality management operation information and the user 600 policy check unit stored in the storage medium Managing the user view information identified by the data structure checking unit 635 according to a data management process on the database quality management framework shown in FIG. 1 based on the quality management policy information confirmed by 615. The detailed description thereof will be described in detail with reference to the following flowchart.

3 is a diagram illustrating an overview data model according to an embodiment of the present invention.

In more detail, Figure 3 illustrates an overview data model managed by the Chief Information Officer (CIO) on the database quality management framework, and if the person skilled in the art to which the present invention pertains, Figure 3 With reference to the database quality management framework can be inferred various implementation methods for the overview data model managed by the Chief Information Officer (CIO), detailed description thereof will be omitted for convenience.

4 illustrates a conceptual data model according to an embodiment of the present invention.

In more detail, Figure 4 illustrates a conceptual data model managed by a data management officer (DA) on the database quality management framework. If those skilled in the art to which the present invention pertains, Figure 4 Since various implementation methods for the conceptual data model managed by the data manager (DA) on the database quality management framework can be inferred, a detailed description thereof will be omitted for convenience.

5 is a diagram illustrating a data reference model according to an embodiment of the present invention.

In more detail, FIG. 5 illustrates a data reference model managed by a data management officer (DA) on the database quality management framework, and a person having ordinary knowledge in the art to which the present invention pertains, FIG. Since various implementation methods for the data reference model managed by the data manager (DA) on the database quality management framework can be inferred, a detailed description thereof will be omitted.

6 illustrates a logical data model according to an embodiment of the present invention.

In more detail, FIG. 6 illustrates a logical data model managed by a modeler on the database quality management framework. Those skilled in the art to which the present invention pertains may refer to the database quality with reference to FIG. Since various implementation methods for the logical data model managed by the modeler can be inferred on the management framework, a detailed description thereof will be omitted for convenience.

7 is a diagram illustrating a physical data model according to an embodiment of the present invention.

In more detail, Figure 7 illustrates a physical data model managed by a database administrator (DBA) on the database quality management framework. If the person skilled in the art to which the present invention pertains, refer to the Figure 7 Therefore, various implementation methods for a physical data model managed by a database administrator (DBA) may be inferred on the database quality management framework, and thus a detailed description thereof will be omitted for convenience.

8 illustrates a table code of a database according to an embodiment of the present invention.

In more detail, Figure 8 illustrates a table code of a database managed by a database administrator (DBA) on the database quality management framework. If the person skilled in the art to which the present invention pertains, the figure 8 With reference to the database quality management framework can be inferred various implementation methods for the table code of the database managed by the database administrator (DBA), detailed description thereof will be omitted for convenience.

9A and 9B illustrate database tables according to an embodiment of the present invention.

In more detail, FIGS. 9A and 9B illustrate a database table managed by a database manager (DBA) through the table code shown in FIG. 8 on the database quality management framework. Those skilled in the art will be able to infer various implementation methods for a database table managed by a database administrator (DBA) on the database quality management framework with reference to FIGS. 9A and 9B. Omit for convenience.

10 illustrates a user view according to an embodiment of the present invention.

More specifically, FIG. 10 illustrates a user view managed by a user on the database quality management framework. If the person of ordinary skill in the art belongs to the present invention, the database quality management will be described with reference to the present FIG. Since various implementation methods for a user view managed by a user on the framework may be inferred, a detailed description thereof will be omitted for convenience.

11 is a diagram illustrating a standard data management screen according to an embodiment of the present invention.

More specifically, Figure 11 illustrates the management of the standard data managed by the data management officer (DA) on the database quality management framework, if the person skilled in the art to which the present invention belongs, Referring to FIG. 11, various implementation methods for managing the standard data by the data manager DA may be inferred on the database quality management framework, and thus a detailed description thereof will be omitted.

12 is a diagram illustrating a model data management screen according to an embodiment of the present invention.

In more detail, FIG. 12 illustrates an example of managing model data managed by a modeler on the database quality management framework. Those skilled in the art to which the present invention pertains may refer to FIG. 12. Since a modeler may infer various implementation methods for managing the model data on the database quality management framework, a detailed description thereof will be omitted for convenience.

13A and 13B are views illustrating management data management screens according to an embodiment of the present invention.

13a and 13b illustrate more details of managing management data managed by a database administrator (DBA) on the database quality management framework, and a person having ordinary knowledge in the technical field to which the present invention belongs, Referring to FIGS. 13A and 13B, various implementation methods for managing the management data by a database administrator (DBA) on the database quality management framework may be inferred, and thus a detailed description thereof will be omitted.

According to the present invention, the quality management for the quality management target DBMS 100 based on the database quality management framework as described above, in the work flow related to the DBMS 100, the quality management target DBMS 100 If a business plan is established, the new system for the quality management target DBMS 100 is developed, and if a failure occurs in the existing quality control target DBMS 100, the quality management target DBMS 100 ), Such as when distributing the application corresponding to the).

Hereinafter, when a business plan for the quality control target DBMS 100 is established, a process of quality control for the quality control target DBMS 100 is described based on a database quality management framework.

14A is a diagram illustrating a data quality control main process according to an embodiment of the present invention.

In more detail, FIG. 14A illustrates data standard management, data model management, data flow management, and database from data management policy establishment for operation and management of high quality data when a business plan for the quality management target DBMS 100 is established. A series of data management activities ranging from management, data utilization management, and requirements management to a systematic flow that defines and evaluates data in the form most appropriate for the organizational environment of an organization or company by understanding the systematic process for high quality data management. It is aimed at supporting the establishment of a series of processes such as data management, change, and management. The main subjects of the data quality control main process are data management policy, data standard management, data model management, data flow management, database management, and data management. Utilization management, requirements Management and so on.

Those skilled in the art to which the present invention pertains may refer to and / or modify this drawing 14a to infer various implementation methods for the data quality control main process, but the present invention is directed to all of the inferred It includes all implementation methods, and is not limited to the implementation method shown in FIG. 14A.

Referring to Figure 14a in accordance with an embodiment of the present invention, the database quality control subject is the chief information officer (CIO), data management officer (DA), modeler, database manager (DBA) and user on the database quality management framework. Characterized in that comprises a.

Here, the chief information officer (CIO) is in charge of the overall data management, data management policy formulation and coordination of issues between data managers, the data management officer (DA) is the overall data change management general, enterprise data integration model management, And the development and coordination of data standards, and the modeler is responsible for coordinating and integrating data requirements and issues in the functional areas, performing data modeling based on the business requirements of the functional areas, and confirming and applying standards. The database manager (DBA) is responsible for database design, configuration management of the database and data, monitoring, tuning and security management of the database, and the user requests utilization of data and operational analysis data and additional requirements for the data. It is in charge of the back.

Referring to FIG. 14a, the chief information officer (CIO) establishes a data management policy for the data quality management (s210), where the data management policy is established to achieve a company's vision and goals based on a business plan. It is the task of defining the data acquisition plan necessary for the purpose and the system and plan for effectively managing and maintaining the acquired data. Detailed work details define processes related to database quality, select work subjects to perform the defined processes, and establish an education system to cultivate the ability of the selected work subjects to perform the work smoothly. Etc.

In the detailed step of establishing the data management policy, when the data management policy needs to be established and changed according to changes in the environment of the business or IT, a data management policy establishment step of collecting the necessary related data and creating policy data (s211). , And / or data management to review and approve the completeness, consistency, feasibility, etc. of the policy by attending the Chief Information Officer (CIO), the relevant users, and the relevant data management officer based on the established policy. A policy review step (s212), and / or a data management policy publication step (s213) for proclaiming the confirmed data management policy, and if necessary to define and modify the data management process according to the policy change, to perform it. It is preferable to make it.

When a business plan for the quality management target DBMS 100 is established, the data manager (DA) defines a data standard for data quality management (s310), where the data standard definition is defined in the corresponding institution. The task of defining the terms and domains, codes, and data-related elements used throughout the enterprise is to define principles based on the standards, meet the user's standardization requirements, and then define the enterprise standards for each standardization element. Include.

The detailed step of defining the data standard may include standardization requirement collection step (s311), and / or standardization principle establishment step (s312), standard word dictionary definition step (s313), and / or standard domain dictionary definition step (s314). And / or standard code definition step s315, and / or standard term definition step s316, and / or data-related element standard definition step s317, and / or data standard review step s318, and / or It is preferable to include a data standard publication step (s319) or the like.

For the data quality management, the data manager DA changes the data standard (s320), wherein the data standard change is performed on the defined data standard (word standard, domain standard, code standard, data related element standard). A change management task that reflects new and additional requests for this information. By modifying the standards for which changes are requested, and analyzing model changes that need to be adjusted as the standards change, the model changes are requested to maintain a standardized data model.

The detailed step of changing the data standard may include a change requirement review step (s321), and / or a standard addition and change step (s322), and / or a standard change impact evaluation step (s323), and / or a standard registration and It is preferable to include the publication step (s324) or the like.

For the data quality management, the data management officer (DA) evaluates a data standard (s330), wherein the data standard evaluation is defined as an operation for evaluating the compliance status of terms, domains, and code standards defined by the organization. This includes checking the compliance of the standards through mapping of the standard and the data model, and improving the non-compliant data by reflecting the results of the cause and change impact analysis.

The detailed step of evaluating the data standard may include a data standard evaluation step (s331), and / or a data standard compliance check step (s332), and / or a change impact analysis step (s333), and / or a data standard non-compliance cause analysis It is preferable that the step (s333), the data purification step (s334) and the like.

For the data quality management, the modeler defines a data model (s410), wherein the data model definition is a conceptual data model, a data reference model, a logical data model, a physical data model designed through a data modeling task when developing a new system. It refers to the work required to create and maintain company-wide. If it is not created and managed previously, a separate work plan should be established to define the same data model as the schema of the database currently in operation.

The detailed step of defining the data model may include a conceptual data model definition step (s411), and / or a data reference model definition step (s412), and / or a logical data model definition step (s413), and / or a physical data model definition. It is preferable to include the step s414 and the like.

For the data quality management, the modeler changes a data model (s420), wherein the data model change is an operation of changing a data model based on a data standard and a data reference model to provide a service suitable for user requirements. When performing change work, change management should be done simultaneously so that conceptual data model, logical data model and physical data model can be related. When changing the model, it is necessary to consider whether the elements defined in other areas are duplicated or changed according to the consistency of data.

The detailed step of defining the data model preferably includes a conceptual data model changing step (s421), a logical data model changing step (s422), and / or a physical data model changing step (s423). .

For the data quality management, the modeler evaluates the data model (s430), wherein the data model evaluation is an operation for evaluating the data model managed by the corresponding organization throughout the concept model-between logical models, logical models-physical Implement data model improvement for errors caused by mapping between models and physical model-to-DB mapping and alignment analysis, and improve DBMS through impact analysis.

The detailed steps for defining the data model include: concept-logical model mapping (s431), logic-physical model mapping (s432), physical model-DB mapping (s433), concept-logical model alignment analysis (s434), logic-physical It is preferable to include model alignment analysis (s435), physical-DB alignment analysis (s436), and the like.

For the data quality control, the modeler defines a data flow (s510), where the

Data flow definition is to control and manage the life cycle of data stored in the target database through manual creation, extraction, conversion, loading, and processing of source data (document, text, DB, etc.). This includes batching unstructured data.

The detailed steps of defining the data flow include: data extraction (transformation) definition definition (s511), source data analysis (s512), source data extraction (transformation) design (s510), source data extraction (transformation) test (s514), Source data extraction (conversion) verification (s515), source data extraction (conversion) module reflection (s516), source data extraction (conversion) monitoring (s517) and the like is preferably made.

For the data quality management, the modeler evaluates the data flow (s520), where the

Data flow evaluation is the task of evaluating the consistency of data stored and managed as target data by setting source data. It establishes data flow check criteria and indicators, checks the consistency of data, analyzes error data and reflects the results of impact analysis. To make improvements.

The detailed step of defining the data flow includes deriving data flow check criteria (s521), generating data flow check indicators (s522), checking data consistency (s523), analyzing error data (s524), analyzing change impacts (s525), and data. It is preferable to include tablet (s526) and the like.

For the data quality management, the modeler manages data utilization (s710), wherein the data utilization management measures quality and analyzes quality by selecting measurement data and quality indicators to check whether data is used or to increase utilization. If the quality is not met, the cause is analyzed to cause the person in charge to take action.

The detailed steps of defining the data flow include collecting core data (s711), establishing utilization measurement standards (s712), measuring data utilization (s713), analyzing utilization degradation factors (s714), preparing improvement plans (s715), and performing improvement activities. (s716), improvement activity evaluation (s717), and the like.

The database manager (DBA) defines a database (s610) for the data quality management, wherein the database definition refers to regular and irregular work required to stably operate and maintain the database, and includes a database suitable for a data model. And backup, security, recovery, and performance management.

The detailed steps of defining the database include database creation (s611), backup cycle and schedule definition (s612), database backup execution (s613), data security target selection (s614), data security application (s615), and data security training. (s616) and the like are preferable.

The database manager (DBA) changes the database (s620) for the data quality management, wherein the database change refers to a task of changing the database based on the changed data model according to the requirements.

The detailed step of changing the database may include database improvement (s621), data security improvement (s622), database recovery (s623), test database change (s624), and operation database transfer (s625). .

The database manager (DBA) evaluates the database for the data quality management (s630), wherein the database evaluation checks the constraints and object types assigned to the database objects to the objects of the currently set database so that the corresponding rule performs the best performance. To ensure that it is suitable and to prevent errors in the data. For this purpose, after checking the constraints and object types specified for efficiency, the effect of changing constraints or object types in the database to analyze the cause of the inefficient object management type or object type and to improve the inefficiency. Analyze the diagram.

The detailed step of evaluating the database may include database object management efficiency check (s631), inefficiency cause analysis (s632), change impact analysis (s633), and the like.

For the data quality management, the user checks the requirements (s810), where the requirements check is a task of establishing and analyzing the user's requirements in order to eliminate and minimize the risk of business continuity and obstacles in advance. Analyze the impact of database changes on the basis of requirements and define application priorities based on the analysis results. After analyzing the impact and importance of the requirements, determine whether to develop a new system or change an existing one, taking into account size and timing of application.

The detailed step of confirming the requirements is preferably made including a change request (s811), a request convergence (s812), a requirements review (s813) and the like.

In order to control the data quality, the user establishes a change plan (s820), where the change plan determines whether a change of an existing system needs to be a standard change element or a model change element and assigns a worker to perform a corresponding operation. And work to develop a schedule plan. When developing a change plan, work must be carried out to include a change plan for applications and technologies, as well as data-related change plans, so that a comprehensive change plan can be established.

The detailed step of establishing the change plan may include change impact analysis (s821), formulation (s822), change work planning (s823), and the like.

14B illustrates a data management policy establishment process according to an embodiment of the present invention.

In more detail, Figure 14b is a system and plan for effectively maintaining the data acquisition plan and data secured necessary to achieve the company's vision and goals when the business plan for the quality management target DBMS 100 is established Is the task of defining

By establishing a data management policy, the company secures data that meets the institution's vision and goals, and establishes a basic principle and management system that can reliably service the acquired data in the desired form at the desired time. The detailed management target of the data management policy establishment process includes data management principles, data quality management main processes, and data management organizations.

Here, the data management principle refers to the direction of data management included in regulations, plans, and guidelines established for the effective acquisition, maintenance, and management of data, and the data quality management main process is to continuously and stably serve high quality data. It means a process that defines the annual relationship between the processes defined and defined according to the characteristics of each institution.

Means defining the people and organizations responsible for supporting and managing the data management processes defined by each agency.

By establishing a data management policy, systematic and consistent data management is possible by using it as a basis for making decisions about data.

Those skilled in the art to which the present invention pertains may refer to and / or modify this drawing 14b to infer various implementation methods for the data management policy establishment process, but the present invention is directed to all inferred It includes all implementation methods, and is not limited to the implementation method shown in FIG. 14B.

Referring to FIG. 14B according to an embodiment of the present invention, the subject of the data management policy establishment in the data management policy establishment process includes a chief information officer, a data management officer, and a user. It is done.

Here, the Chief Information Officer (CIO) is in charge of data management policy establishment and data management policy publication, and the data management officer (DA) is in charge of supporting data management policy establishment and establishing and improving related processes according to the policy. The user is responsible for review of participation in the proposal policy council.

Referring to FIG. 14B, the chief information officer (CIO) establishes a data management policy for the data quality management (s210), where the data management policy establishment achieves a company's vision and goals based on a business plan. It is the task of defining the data acquisition plan necessary for doing so and the system and plan for effectively managing and maintaining the acquired data. Detailed work details define processes related to database quality, select work subjects to perform the defined processes, and establish an education system to cultivate the ability of the selected work subjects to perform the work smoothly. Etc.

In the detailed step of establishing the data management policy, when the data management policy needs to be established and changed according to changes in the environment of the business or IT, a data management policy establishment step of collecting the necessary related data and creating policy data (s211). , And / or data management to review and approve the completeness, consistency, feasibility, etc. of the policy by attending the Chief Information Officer (CIO), the relevant users, and the relevant data management officer based on the established policy. A policy review step (s212), and / or a data management policy publication step (s213) for proclaiming the confirmed data management policy, and if necessary to define and modify the data management process according to the policy change, to perform it. It is preferable to make it.

14c illustrates a data standard definition process according to an embodiment of the present invention.

More specifically, FIG. 14C illustrates a standard word dictionary and domain dictionary, standard term dictionary, standard code, data related element standard, etc. defined according to data standardization principles when a business plan for the quality management target DBMS 100 is established. Definition and change management in a form suitable for the institution, and data purification and improvement activities by checking compliance with data standards, supporting the design and development of the database, and using and reusing system data standards throughout the system. It aims to maintain consistency and consistency of data by supporting interoperability, data sharing, system integration, business process improvement, and by using common standards throughout the enterprise. The subject matter of the standard evaluation process is the standard word. (word) dictionary, standard domain dictionary, standard term dictionary, standard code, data standard elements, and so on.

Those skilled in the art will be able to infer various implementation methods for the data standard definition process by referring to and / or modifying this drawing 14c, but the present invention is directed to all the inferred implementations. It includes all the methods, and is not limited to the embodiment shown in this figure 14c.

Referring to FIG. 14C according to an embodiment of the present invention, the subject of the data standard definition in the data standard definition process includes a data management officer (DA), a user and a chief information officer (CIO). .

Here, the data manager (DA) is responsible for collecting enterprise standardization requirements, establishing data standardization principles, quasi-word dictionaries, domain dictionaries, code dictionaries, term dictionary definitions, and data standard publications. It is responsible for approval and the Chief Information Officer is responsible for reviewing and approving data standards.

Referring to FIG. 14c, the data management officer (DA) defines a data standard for the data quality control (s310), where the data standard definition refers to terms and domains, codes, and data related elements used in the corresponding institutions. Defining standards across the enterprise includes defining principles according to the standards, collecting the user's standardization requirements, and then defining the enterprise standards for each standardization element.

The detailed step of defining the data standard may include standardization requirement collection step (s311), and / or standardization principle establishment step (s312), standard word dictionary definition step (s313), and / or standard domain dictionary definition step (s314). And / or standard code definition step s315, and / or standard term definition step s316, and / or data-related element standard definition step s317, and / or data standard review step s318, and / or It is preferable to include a data standard publication step (s319) or the like.

The detailed step of defining the data standard is a standard requirement collection step (s311) of reviewing the standards currently used and collecting requirements for establishing enterprise data standards, and / or establishing basic principles prior to defining data standardization. By establishing a standardization principle (s312) to predefine the direction for standardization, standard word dictionary definition step (s313) to extract all the words being used in the institution through existing data models and glossaries, and / or business use A standard domain predefined step (s314) for classifying domains and assigning data types for each domain in consideration of frequency of use and physical characteristics of the data, and / or selecting codes from collected terms and selecting a code value of the current code. Based on the current code to identify the integration target according to integration requirements and integration needs, A standard code definition step (s315) for defining a code and designing a mapping with the current code, and / or forming a standard term based on the word, domain, and code standard when the word, domain, and code standard are defined, and combining words, domain classification, data type length, Standard term definition step (s316) to examine whether the application of the standard based on the code value, etc. is reasonable, and / or the subject area, entity, and attribute relationship name of the logical data model that is the object of the data related element standard. Defining data-related element standards (s317) that define naming conventions such as Subject Areas, Relationships, Database & Instances, Indices, Constraints, Tablespaces, File Names, Script Names, and so on, and / or DA-defined standards. Check word dictionaries, domain dictionaries, code dictionaries, term dictionaries, etc. and ensure that the terms are correctly defined as the terms currently used by your organization. Check and approve. In the case of code dictionaries, it is necessary to check whether the offership is correctly defined and to review the data standards for change inaccuracies (s318), and / or to distribute the confirmed data standards so that they can be applied to the enterprise system. It is preferable to include a data standard review step (s319) for performing a training task for understanding and applying the data.

14d illustrates a data standard evaluation process in accordance with an embodiment of the present invention.

More specifically, FIG. 14D illustrates a standard word dictionary and domain dictionary, standard term dictionary, standard code, data related element standard, etc. defined according to data standardization principles when a business plan for the quality management target DBMS 100 is established. Definition and change management in a form suitable for the institution, and data purification and improvement activities by checking compliance with data standards, supporting the design and development of the database, and using and reusing system data standards throughout the system. It aims to maintain consistency and consistency of data by supporting interoperability, data sharing, system integration, business process improvement, and by using common standards throughout the enterprise. The subject matter of the standard evaluation process is the standard word. (word) dictionary, standard domain dictionary, standard term dictionary, standard code, data standard elements, and so on.

Those skilled in the art to which the present invention pertains may refer to and / or modify this drawing 14d to infer various implementation methods for the data standard evaluation process, but the present invention implements all the inferred implementations. It includes all the methods, and is not limited to the embodiment shown in this figure 14d.

Referring to FIG. 14D according to an embodiment of the present invention, the subject of data evaluation in the data standard improvement process includes a data manager (DA), a modeler and a database manager (DBA).

Here, the data manager (DA) is responsible for data standards (data model mapping), data standards compliance check (data standards-concept data model standards check), change impact analysis (data standard change impact analysis), The modeler is responsible for data standards (data model mapping), data standard compliance check (data standard-logic, physical data model compliance check), change impact analysis (data model change impact analysis), and the database manager (DBA). ) Is responsible for data standards (database object mapping), data standard compliance checks (data standard-database object standard compliance checks), and change impact analysis (database structure change impact analysis).

Referring to FIG. 14D, the data management officer (DA) evaluates a data standard for the data quality control (s330), wherein the data standard evaluation is in compliance with terms, domains, and code standards defined throughout the organization. This includes evaluating standards for compliance with the defined standards and data models, and performing improvements based on the analysis of cause and change impacts for non-compliant data.

The detailed step of evaluating the data standard may include a data standard evaluation step (s331), and / or a data standard compliance check step (s332), and / or a change impact analysis step (s333), and / or a data standard non-compliance cause analysis It is preferable that the step (s333), the data purification step (s334) and the like.

The detailed step of evaluating the data standard may include mapping the data standard and the data model (s331), and / or the data standard reflecting the term standard, domain standard, and naming convention standard to the data model (concept, logic, and physics). Data standard compliance check step (s332) for checking whether the data standard is compliant between data objects (data model, database object), and / or change impact analysis for analyzing the impact on the non-compliance part of the data standard in the above checking process. Analysis step (s333), and / or data standard non-compliance cause analysis step (s334) for analyzing the cause of non-compliance by checking whether the data standard is observed for actual data values, and / or the above data standard It includes a data refinement step (s335) to modify the data through a number of analysis work for the data that did not comply with Preferable.

14E illustrates a data model operating process according to an embodiment of the present invention.

More specifically, FIG. 14E illustrates a data model similar to a work procedure and a database system structure in which a data structure changed by data requirement management is reflected in a model when a business plan for the quality management target DBMS 100 is established. The data model is intended to provide a data service optimized for the organization's business purpose and to systematically manage to construct and maintain a database, and to detail the data model operation process. Management targets include conceptual data models, data reference models, logical data models, and physical data models.

Those skilled in the art will be able to infer various implementation methods for the data model operation process by referring to and / or modifying this drawing 14e, but the present invention is intended to implement all the inferred implementations. It includes all the methods, and is not limited to the embodiment shown in this figure 14e.

Referring to FIG. 14E according to an embodiment of the present invention, the subject of data model operation in the data standard definition process includes a data manager (DA), a modeler and a database manager (DBA).

The data model operation process enables the understanding of the enterprise data structure through the correlation analysis of logical and physical data models based on the conceptual data model, and the same model as the current database through the correlation analysis between the physical data model and the database. The acquisition enables maintenance and systematic management of enterprise-wide databases, and by utilizing a data reference model, a certain level of data model and high-quality data service are possible.

The data manager DA is responsible for defining a conceptual data model, reviewing a logical data model, defining a data reference model, changing a conceptual data model, etc. The modeler is responsible for defining a logical data model, changing a logical data model, and the like. The database manager (DBA) is responsible for defining a physical data model, changing a physical data model, and the like.

Referring to FIG. 14E, the modeler defines a data model for the data quality management (s410), wherein the data model definition is a conceptual data model, a data reference model, and logical data designed through a data modeling task when developing a new system. This refers to the work required to create and maintain models and physical data models throughout the enterprise. If it is not created and managed previously, a separate work plan should be established to define the same data model as the schema of the database currently in operation.

The detailed steps for defining the data model operation may include conceptual data model definition step s411, and / or data reference model definition step s412, and / or logical data model definition step s413, and / or physical data model. It is preferable to include the definition step (s414) and the like.

The detailed step of defining the data model operation is to define the data subject areas necessary to establish the vision of each institution, and to design the enterprise information in a non-overlapping and scalable manner rather than the detailed details, and the subject areas of the data and the core data set and data. A conceptual data model definition step (s411) for defining a relationship between sets and supporting data structural alignment between a detailed logical data model and a physical data model to be defined in the future (s411), and / or a work area or a subject area standard. A data reference model definition step (s412), which defines a data model that is reusable by displaying data sets and management items, and references a previously validated data model to increase the accuracy and reuse rate of the data model and to guarantee a certain level of design quality (s412). And / or detail all data structures in the business based on business rules If you focus on extracting the interface between other subject areas when defining the conceptual data model, you should refer to the data reference model and data standard. Based on the interface, the design work focuses on the relations in the subject area, and when the definition of the logical data model is completed, the review work with the DA and the user is performed to review whether the data is designed to meet the requirements of the business. A model definition step (s413), and / or a physical data model definition step (s414) for performing detailed design work for optimal performance in consideration of the physical characteristics of the target database based on the logical data model and the data standard, And / or change models according to the nature of user requirements If the change size is large (interface coordination between different subject areas, change of key entity type, change of relationship between key entity types), change of conceptual data model occurs and conceptual data When the model is changed, the conceptual data model change step (s421) in which a change of the logical data model and the physical data model is necessarily performed, and / or a small scale change without changing the conceptual data model or changing the conceptual data model (topic area) Interface adjustment, entity type change, relationship between entity types, and attribute change) are requested, when the data standard is changed, the logical data model is changed, and when the logical data model is changed, the same type is applied to other subject areas. Check for redundancy and data table by checking if dataset exists Logical data model change step (s422) for maintaining a standardized model with reference to the quasi and data reference models, and / or the optimized request by referring to the logical data model and data standards, the physical characteristics of the database, etc. It is preferable to include a physical data model change step (s423) for performing a physical data model change operation so as to exhibit the performance of the

14E illustrates a data model improvement process according to an embodiment of the present invention.

In more detail, FIG. 14E illustrates a work procedure for reflecting the data structure changed by data requirements management in the model and a work procedure for maintaining the data model in the same manner as the database system structure. Its purpose is to systematically manage to provide optimized data services for the purpose and to construct and maintain a database. The detailed management targets in the data model improvement process include conceptual data models, data reference models, logical data models, and physical data. Including the model.

Those skilled in the art will be able to infer various implementation methods for the data model improvement process by referring to and / or modifying this drawing 14e, but the present invention is directed to all the inferred implementations. It includes all the methods, and is not limited to the embodiment shown in this figure 14e.

Referring to FIG. 14E according to an embodiment of the present invention, the subject of data model improvement in the data standard definition process includes a data manager (DA), a modeler and a database manager (DBA).

Through the data model improvement process, it is possible to understand the enterprise data structure through the correlation analysis of logical and physical data models based on the conceptual data model, and the same model as the current database through the correlation analysis between the physical data model and the database. The acquisition enables maintenance and systematic management of enterprise-wide databases, and by utilizing a data reference model, a certain level of data model and high-quality data service are possible.

Here, the data manager DA is responsible for concept-logical data model mapping, concept-logical data model alignment analysis, and the modeler is responsible for logical-physical data model mapping, logic-physical data model alignment analysis, and the like. It is responsible for the physical data model-DB mapping, physical data model-DB analysis.

Referring to FIG. 14E, for the data model improvement process, the modeler evaluates a data model (s430), wherein the data model evaluation is a task of evaluating a data model managed by the corresponding organization. Implement data model improvement for errors caused by mapping between models, logical models-between physical models, physical models-between DBs, and alignment analysis, and improve DBMS through impact analysis. .

The detailed steps for defining the data model include: concept-logical model mapping (s431), logic-physical model mapping (s432), physical model-DB mapping (s433), concept-logical model alignment analysis (s434), logic-physical It is preferable to include model alignment analysis (s435), physical-DB alignment analysis (s436), and the like.

The detailed step of defining the data model is to generate structural connection information between the conceptually generated data set or management item and the logical data model. From the data architecture point of view, each object of the conceptual data model and each object between the logical data model The conceptual connection logic between the physical data model in consideration of the physical data of the database and the model data structure of the task based on the concept-logical model mapping step (s431), and / or the business rules for establishing the alignment between them. logic to set the alignment-physical model mapping step (s432), and / or establishing structural alignment between the physical data model (final design drawing) and DBMS catalog (architecture) information (s433), And / or the model defined in the conceptual data model is not specifically defined in the actual logical data model. It analyzes the difference (gap) between the step (s434), and / or logical data model and the physical data model for analyzing the difference (gap), such as to check that the model exists. Analyze the change from the modeler perspective to perform the change on the corresponding data model (s435), and / or analyze the gap between the physical data model and the actual DB. By doing so, it is preferable to include a step (s436) and the like analyzing whether there is a DB object that is not represented in the model.

14f illustrates a data flow management process in accordance with an embodiment of the present invention.

More specifically, FIG. 14F illustrates a target database when a business plan for the quality management target DBMS 100 is established, by generating source data (document, text, DB, etc.) by hand or extracting, converting, and loading the target database. It means to manage the data stored in the organization and to process it, and to manage the life cycle in which the data managed by each organization is created, changed, and utilized. The detailed management object in the data flow management process includes source work data, operational work data, analysis work data, flow management data, and the like.

Those skilled in the art to which the present invention pertains may refer to and / or modify this drawing 14f to infer various implementation methods for the data flow management process. All the methods are included, and the method is not limited to the embodiment shown in Fig. 14F.

The data flow management process enables data extraction and transformation, monitoring of loading and systematic management to increase the accuracy and stability of the data and to improve the reliability of the data.

Referring to FIG. 14f according to an embodiment of the present invention, the subject of the data flow management in the data flow management process includes a data manager (DA), a modeler and a database manager (DBA), and a user. do.

Here, the data manager (DA) is responsible for reviewing the source data extraction (transformation) requirements, approving whether the source data extraction (transformation) module is applied, monitoring the source data extraction (transformation) result, and the modeler. It is responsible for analyzing source data (tables and columns) for conversion, module design for source data extraction (transformation), source data extraction (transformation) testing, monitoring source data extraction (transformation) results, etc. (DBA) is responsible for reflecting the system of the source data extraction (transformation) module, and the user is responsible for defining source data extraction (transformation) requirements and verifying the source data extraction (transformation) result.

Referring to FIG. 14f, for the data quality management, the modeler defines a data flow (s510), where the data flow definition generates, extracts, converts, and loads original data (document, text, DB, etc.) by hand. In addition, the process of controlling and managing the life cycle of data stored in the target database through processing includes periodic irregular batching and batching of structured unstructured data.

Detailed steps for managing the data flow may include defining data extraction (transformation) requirements (s511), analyzing source data (s512), designing source data extraction (transformation) (s510), testing source data extraction (transformation) (s514), Source data extraction (conversion) verification (s515), source data extraction (conversion) module reflection (s516), source data extraction (conversion) monitoring (s517) and the like is preferably made.

The detailed step of managing the data flow defines the requirements to extract (transform) data from the requirements received from the user for business operation and load it into the database, and the DBA reviews the data policy in the enterprise architecture view when reviewing the requirements. In the step of defining data extraction (transformation) requirements (s511) that define whether and how to reflect the standard, and / or analyzing the source data, Modeler decides to extract (transform) the source data and load it into the database. For the source data analysis step (s512), which analyzes the contents of the tables and columns from the source data perspective against the determined requirements, and / or the source data extraction (transformation) design, Modeler designs the transformation and loading logic of the source data. Source data extraction (transform) design step (s513), and / or source data extraction (change) test for M The odeler extracts the source data for source data extraction (conversion) test step (s514), and / or source data extraction (conversion) verification, which loads the source data into the target database in test format according to the extraction (transformation) design. Source data extraction (transformation) verification step (s515), and / or source data extraction (transformation) module reflecting that the requirements are accurately reflected in the target database based on the contents created in the (conversion) test to confirm that the data is loaded. In order for the DBA to reflect the source data extraction (transformation) module applying the verified source data extraction (transformation) change to the operating environment (s516), and / or modeler operates for monitoring the source data extraction (transformation). The source data extraction (transformation) module applied to the environment is periodically monitored and the results are reported to the DA. It is preferred which comprises a source to extract data (conversion) monitoring step (s517), etc.

Figure 14g illustrates a database operating process in accordance with an embodiment of the present invention.

In more detail, Figure 14g is a system for managing the operations necessary for the stable operation and management of the database required for smooth data service, if the business plan for the quality management target DBMS (100) is established, backup, security, tuning, It refers to operations such as monitoring, and the database management operation can continuously create, change, secure, improve performance, and manage backup of the database so that the database and the data stored in the database can be reliably serviced without errors and damages. For the purpose of systematization, the database management process includes detailed management targets including standard data, model data, management data, and business data.

Those skilled in the art will be able to infer various implementation methods for the database operation process by referring to and / or modifying this drawing 14g, but the present invention is directed to all implementation methods that are inferred. It includes all, and is not limited to the embodiment shown in Figure 14g.

Through the database management process, the database management system enables the user to prepare the foundation for stable and continuous business activities by accurately and stably serving the desired data in the desired form at the desired time without any error or damage of the data.

Referring to FIG. 14G according to an embodiment of the present invention, the subject of the database operation in the database operation process includes a user, a database administrator (DBA), and the like.

Here, the user is responsible for testing the change program, and the database manager (DBA) is responsible for creating a database, scheduling backups and performing backups, recovering, selecting and securing data security targets, applying and improving data security, improving database performance, Responsible for database changes and migration.

Referring to FIG. 14G, the database manager (DBA) defines a database (s610) for the data quality management, where the database definition refers to regular and irregular work required to stably operate and maintain the database. Database configuration and backup suitable for data model, security, recovery, performance management, etc.

The detailed operation of the database may include creating a database (s611), defining a backup cycle and schedule (s612), performing a database backup (s613), selecting a data security target (s614), applying data security (s615), and performing data security training ( s616), etc. are preferable.

The detailed operation of the database may include a database generation step (s611) of configuring a database in consideration of the physical characteristics of the database based on a DDL statement based on a data model designed according to a business requirement, and / or data in use even if any obstacle occurs. Backup is performed by referring to a backup cycle and schedule definition step (s612) for defining a backup cycle and schedule so as to allow full recovery of the backup, and / or a schedule table for each backup cycle. The backup operation procedure checks whether the database is in a normal state of operation and allocates a time when there is no batch operation, and performs a database backup step (s613) for performing a backup, and / or evaluates the identification and value of assets to be protected. Data security target selection step (s614), and / or applying security based on the importance of each security target, to perform the analysis of vulnerabilities and threat factors present in the system. The data security application stage (s615) to apply comprehensive security such as operating system security, database security, application system security, and PC security, and / or data security policy established by each institution should be conducted at least once a year for all members. Data security training system to systematize high quality education through evaluation work It is preferred which comprises a (s616), etc.

Referring to FIG. 14g, the database manager (DBA) changes a database (s620) to change the database, where the database change is performed to change a database based on a changed data model according to requirements.

The detailed step of changing the database may include database improvement (s621), data security improvement (s622), database recovery (s623), test database change (s624), operational database transfer (s625), and the like. .

The detailed step of changing the database may include a performance improvement step required by a user of the institution, a database performance step (s621) of handling static and dynamic numeric requests, and / or damage to important data, Data security improvement step (s622) to improve the security device when the requirements for physical access control (suggested area, controlled area, etc.) and usage control (authentication, encryption, firewall, etc.) for tampering, theft, leakage, etc. occurs, and DDL created on the basis of the data model changed according to the requirements presented by the database recovery step (s623), and / or the requirements presented by the change request, for recovering the existing backed up data due to the overall damage to the data and / or errors due to obstacles, etc. Based on the statement, the test database considering the physical characteristics of the database has the same form as the modified data model. A test database change step to change (s624), and / or a unit test to check the problem with the application based on the changes made in the test database, an integration test to test the interface with other applications, and a user test to confirm the user's satisfaction. If the stability and accuracy is secured after performing such as, it is preferable to include the operation database transfer step (s625), etc. reflecting the change history in the operation database.

14h illustrates a data utilization management process according to an embodiment of the present invention.

More specifically, Figure 14h shows the quality of the data management target DBMS (100) when the business plan is established, in order to check the availability of the data or to increase the utilization of the measurement target data and quality indicators to measure and analyze the quality If the quality is not met, the cause is analyzed to cause the person in charge to take action. V Check the data that is not utilized by the application to improve the DB environment and evaluate the quality of the data with high business importance. In order to improve the utilization of the data by improving and improving the data, the database management process includes detailed data that directly affects the company's customers, processes, market environment and financial information.

Those skilled in the art to which the present invention pertains may refer to and / or modify this drawing 14h to infer various implementation methods for the data utilization management process, but the present invention is intended to implement all the inferred implementations. It includes all the methods, and is not limited to the embodiment shown in this figure 14h.

Analyzing and improving the cause of data deterioration by the data utilization management process has the effect of improving the quality and usability of continuous data.

Referring to FIG. 14h according to the embodiment of the present invention, the subject of the data utilization management in the data utilization management process includes a data manager (DA), a modeler, a user, and the like.

Here, the data manager (DA) is responsible for establishing core data collection and utilization measurement standards, evaluating improvement activities, etc. The modeler is responsible for measuring data utilization, analyzing utilization degradation factors, establishing improvement plans, and performing improvement activities. For example, the user is responsible for presenting data utilization opinions.

Referring to FIG. 14h, the modeler manages data utilization for data quality management (s710), wherein the data utilization management selects data to be measured and quality indicators to check whether data is used or to increase utilization. When measuring and analyzing quality does not meet the quality, the cause is analyzed to cause the person in charge to take action.

The detailed steps of the data utilization management, core data collection (s711), utilization measurement criteria establishment (s712), data utilization measurement (s713), utilization degradation factor analysis (s714), improvement measures (s715), improvement activities performed ( s716), improvement activity evaluation (s717), and the like.

The detailed step of managing data utilization includes preparing and selecting selection data to be improved, and a core data collection step (s711) for adjusting the amount of measurement data in consideration of work load and system load, and / or utilization of data. Establish quantitative metrics and establish data utilization improvement targets to evaluate future improvement work (S712), and / or data to perform utilization evaluation based on data utilization metrics Utilization measurement step (s713), and / or utilization degradation factor analysis step (s714), and / or utilization, which derives from the perspective of generating, updating, converting, and utilizing data the business and IT causes that caused the data to be degraded. In the preparation of improvement plans for each cause of degradation (s715), and / or the action plan for approved improvement plans and the improvement plans derived for each cause. Therefore, in the process of promoting improvement activities and / or performing improvement activities (s716), and / or evaluating improvement activities, data exceeding the measurement targets are excluded from the improvement items, or the target values are adjusted. It is desirable to include the improvement activity evaluation step (s717) that can be summarized so that it can be used for future activities.

14I illustrates a requirements management process in accordance with an embodiment of the present invention.

More specifically, FIG. 14i refers to a task of collecting, classifying, and reflecting a user's request across data and related applications and systems when a business plan for the quality management target DBMS 100 is established. It aims to improve user satisfaction and enable high-quality service by comprehensively reviewing and verifying the information requirements of the company, and improving and reflecting the system to meet the requirements. This includes the functional improvement requirements, performance improvement requirements and security improvement requirements.

Those skilled in the art will be able to infer various implementation methods for the requirement management process by referring to and / or modifying this drawing 14i, but the present invention is directed to all implementations inferred from the above. All the methods are included, and the present invention is not limited to the implementation method shown in FIG.

The requirement management process has the effect of increasing user satisfaction through systematic and comprehensive processing of user requirements and securing traceability of requirements.

Referring to FIG. 14i in accordance with an embodiment of the present invention, the subject of the requirements management in the requirements management process includes a data manager (DA), a modeler, a user and a service desk.

Here, the data manager (DA) is responsible for formalizing the reviewed requirements, defining the requirements processing type, and modifying and establishing a change plan through analysis of the impact of change, and the modeler determines whether the requirements can be reviewed and processed. The user is in charge of change requests and the service desk is responsible for collecting requirements.

Referring to FIG. 14i, for the data quality control, the user checks the requirements (s810), where the requirements check is carried out to remove the requirements of the user in order to eliminate and minimize the risk of business continuity and obstacles in advance. It is the work of establishing and analyzing. Analyze the impact of database changes on the basis of requirements and define application priorities based on the analysis results. After analyzing the impact and importance of the requirements, determine whether to develop a new system or change an existing one, taking into account size and timing of application.

The detailed requirements management step preferably includes a change request (s811), a request convergence (s812), a requirement review (s813), and the like.

The detailed step of managing the requirements may include a change request step (s811) for requesting a request for change through an application for change of requirements such as an external interface and a function, performance, security, etc. generated by the user using the system of the institution; and And / or a requirements gathering step (s812) that verifies that the requested change request has been collected from the user and accurately defined in accordance with the rules for making a change application, and designates a modeler to review the requirements, and / or the requested request. It is preferable to include a requirement review step (s813) for checking the data, standards, systems, etc. related to the matter to determine whether it can be processed and requesting formalization through DA if possible.

In order to manage the requirements, the user establishes a change plan (s820), where the change plan determines whether a change of an existing system needs to be a standard change element or a model change element and assigns a worker to perform the corresponding work. And work to develop a schedule plan. When developing a change plan, work must be carried out to include a change plan for applications and technologies, as well as data-related change plans, so that a comprehensive change plan can be established.

The detailed step of establishing the change plan may include change impact analysis (s821), formulation (s822), change work planning (s823), and the like.

The detailed step of establishing the change plan may include a change impact analysis step (s821) for deriving a design document, an application, a database, etc. that affect the change based on the change request details, and / or change processing through the impact analysis. The formalization step (s822), which assembles and formalizes the relevant personnel who are required, and consults with those persons to determine whether to approve the change and how to handle the change, and / or the impact assessment report to identify the relevant work area and related system details. It is preferable to include a work schedule planning step (s823) and the like based on.

Hereinafter, when a problem that causes a drop in service quality occurs in the quality control target DBMS 100 due to abnormal application operation, data error, or system error, the quality control target DBMS 100 is based on a database quality management framework. ), Which illustrates the process of quality control.

15A is a diagram illustrating a data quality control main process according to an embodiment of the present invention.

In more detail, FIG. 15A illustrates data standard management, data model management, data flow management, database management, and data management from data management policy establishment for operation and management of high quality data when a failure occurs in the quality management target DBMS 100. It is a systematic flow of data management activities ranging from utilization management and requirements management to understanding the systematic process for high quality data management. It aims to support the establishment of the same series of processes, and the main subjects of the data quality management main process are data management policy, data standard management, data model management, data flow management, database management, data utilization management, Requirements management, It achieved by also.

Those skilled in the art to which the present invention pertains will be able to infer various implementation methods for the data quality control main process by referring to and / or modifying this figure 15a, but the present invention is inferred from all It includes all implementation methods and is not limited to the implementation method shown in FIG. 15A.

Referring to FIG. 15A according to an embodiment of the present invention, the database quality control subject may be a chief information officer, a data manager, a modeler, a database manager, a user, and the like. Characterized in that comprises a.

Here, the chief information officer (CIO) is in charge of the overall data management, data management policy formulation and coordination of issues between data managers, the data management officer (DA) is the overall data change management general, enterprise data integration model management, And the development and coordination of data standards, and the modeler is responsible for coordinating and integrating data requirements and issues in the functional areas, performing data modeling based on the business requirements of the functional areas, and confirming and applying standards. The database manager (DBA) is responsible for database design, configuration management of the database and data, monitoring, tuning and security management of the database, and the user requests utilization of data and operational analysis data and additional requirements for the data. It is in charge of the back.

Referring to FIG. 15A, the chief information officer (CIO) establishes a data management policy for the data quality management (s210), where the data management policy is established to achieve a company's vision and goals based on a business plan. It is the task of defining the data acquisition plan necessary for the purpose and the system and plan for effectively managing and maintaining the acquired data. Detailed work details define processes related to database quality, select work subjects to perform the defined processes, and establish an education system to cultivate the ability of the selected work subjects to perform the work smoothly. Etc.

In the detailed step of establishing the data management policy, when the data management policy needs to be established and changed according to changes in the environment of the business or IT, a data management policy establishment step of collecting the necessary related data and creating policy data (s211). , And / or data management to review and approve the completeness, consistency, feasibility, etc. of the policy by attending the Chief Information Officer (CIO), the relevant users, and the relevant data management officer based on the established policy. A policy review step (s212), and / or a data management policy publication step (s213) for proclaiming the confirmed data management policy, and if necessary to define and modify the data management process according to the policy change, to perform it. It is preferable to make it.

For the data quality management, the data manager (DA) defines a data standard (s310), where the data standard definition defines a standard for terms and domains, codes, and data-related elements used in a corresponding organization. This includes defining principles according to standards, collecting user standardization requirements, and then defining enterprise standards for each standardization element.

The detailed step of defining the data standard may include standardization requirement collection step (s311), and / or standardization principle establishment step (s312), standard word dictionary definition step (s313), and / or standard domain dictionary definition step (s314). And / or standard code definition step s315, and / or standard term definition step s316, and / or data-related element standard definition step s317, and / or data standard review step s318, and / or It is preferable to include a data standard publication step (s319) or the like.

When a failure occurs in the quality management target DBMS 100, a change plan for the DBMS 100 is established by the user, and in response to the data quality management, the data manager DA is a data standard. In this case, the data standard change refers to a change management operation reflecting new and additional requests for the defined data standard (word standard, domain standard, code standard, data related element standard). By modifying the standards for which changes are requested, and analyzing model changes that need to be adjusted as the standards change, the model changes are requested to maintain a standardized data model.

The detailed step of changing the data standard may include a change requirement review step (s321), and / or a standard addition and change step (s322), and / or a standard change impact evaluation step (s323), and / or a standard registration and It is preferable to include the publication step (s324) or the like.

For the data quality management, the data management officer (DA) evaluates a data standard (s330), wherein the data standard evaluation is defined as an operation for evaluating the compliance status of terms, domains, and code standards defined by the organization. This includes checking the compliance of the standards through mapping of the standard and the data model, and improving the non-compliant data by reflecting the results of the cause and change impact analysis.

The detailed step of evaluating the data standard may include a data standard evaluation step (s331), and / or a data standard compliance check step (s332), and / or a change impact analysis step (s333), and / or a data standard non-compliance cause analysis It is preferable that the step (s333), the data purification step (s334) and the like.

For the data quality management, the modeler defines a data model (s410), wherein the data model definition is a conceptual data model, a data reference model, a logical data model, a physical data model designed through a data modeling task when developing a new system. It refers to the work required to create and maintain company-wide. If it is not created and managed previously, a separate work plan should be established to define the same data model as the schema of the database currently in operation.

The detailed step of defining the data model may include a conceptual data model definition step (s411), and / or a data reference model definition step (s412), and / or a logical data model definition step (s413), and / or a physical data model definition. It is preferable to include the step s414 and the like.

For the data quality management, the modeler changes a data model (s420), wherein the data model change is an operation of changing a data model based on a data standard and a data reference model to provide a service suitable for user requirements. When performing change work, change management should be done simultaneously so that conceptual data model, logical data model and physical data model can be related. When changing the model, it is necessary to consider whether the elements defined in other areas are duplicated or changed according to the consistency of data.

The detailed step of defining the data model preferably includes a conceptual data model changing step (s421), a logical data model changing step (s422), and / or a physical data model changing step (s423). .

For the data quality management, the modeler evaluates the data model (s430), wherein the data model evaluation is an operation for evaluating the data model managed by the corresponding organization throughout the concept model-between logical models, logical models-physical Implement data model improvement for errors caused by mapping between models and physical model-to-DB mapping and alignment analysis, and improve DBMS through impact analysis.

The detailed steps for defining the data model include: concept-logical model mapping (s431), logic-physical model mapping (s432), physical model-DB mapping (s433), concept-logical model alignment analysis (s434), logic-physical It is preferable to include model alignment analysis (s435), physical-DB alignment analysis (s436), and the like.

For the data quality control, the modeler defines a data flow (s510), where the

Data flow definition is to control and manage the life cycle of data stored in the target database through manual creation, extraction, conversion, loading, and processing of source data (document, text, DB, etc.). This includes batching unstructured data.

The detailed steps of defining the data flow include data extraction (transformation) definition definition (s511), source data analysis (s512), source data extraction (transformation) design (s510), and source data extraction (transformation) test (s514). , Source data extraction (conversion) verification (s515), source data extraction (conversion) module reflection (s516), source data extraction (conversion) monitoring (s517), and the like.

For the data quality management, the modeler evaluates the data flow (s520), where the

Data flow evaluation is the task of evaluating the consistency of data stored and managed as target data by setting source data. It establishes data flow check criteria and indicators, checks the consistency of data, analyzes error data and reflects the results of impact analysis. To make improvements.

The detailed step of defining the data flow includes deriving data flow check criteria (s521), generating data flow check indicators (s522), checking data consistency (s523), analyzing error data (s524), analyzing change impacts (s525), and data. It is preferable to include tablet (s526) and the like.

For the data quality management, the modeler manages data utilization (s710), wherein the data utilization management measures quality and analyzes quality by selecting measurement data and quality indicators in order to check whether data is used or to increase utilization. For example, if the quality is not met, the cause is analyzed to cause the person in charge to take action.

The detailed steps of defining the data flow include collecting core data (s711), establishing utilization measurement standards (s712), measuring data utilization (s713), analyzing utilization degradation factors (s714), preparing improvement plans (s715), and performing improvement activities. (s716), improvement activity evaluation (s717), and the like.

The database manager (DBA) defines a database (s610) for the data quality management, wherein the database definition refers to regular and irregular work required to stably operate and maintain the database, and includes a database suitable for a data model. And backup, security, recovery, and performance management.

The detailed steps of defining the database include database creation (s611), backup cycle and schedule definition (s612), database backup execution (s613), data security target selection (s614), data security application (s615), and data security training. (s616) and the like are preferable.

The database manager (DBA) changes the database (s620) for the data quality management, wherein the database change refers to a task of changing the database based on the changed data model according to the requirements.

The detailed step of changing the database may include database improvement (s621), data security improvement (s622), database recovery (s623), test database change (s624), and operation database transfer (s625). .

The database manager (DBA) evaluates the database for the data quality management (s630), wherein the database evaluation checks the constraints and object types assigned to the database objects to the objects of the currently set database so that the corresponding rule performs the best performance. To ensure that it is suitable and to prevent errors in the data. For this purpose, after checking the constraints and object types specified for efficiency, the effect of changing constraints or object types in the database to analyze the cause of the inefficient object management type or object type and to improve the inefficiency. Analyze the diagram.

The detailed step of evaluating the database may include database object management efficiency check (s631), inefficiency cause analysis (s632), change impact analysis (s633), and the like.

For the data quality management, the user checks the requirements (s810), where the requirements check is a task of establishing and analyzing the user's requirements in order to eliminate and minimize the risk of business continuity and obstacles in advance. Analyze the impact of database changes on the basis of requirements and define application priorities based on the analysis results. After analyzing the impact and importance of the requirements, determine whether to develop a new system or change an existing one, taking into account size and timing of application.

The detailed step of confirming the requirements is preferably made including a change request (s811), a request convergence (s812), a requirements review (s813) and the like.

In order to control the data quality, the user establishes a change plan (s820), where the change plan determines whether a change of an existing system needs to be a standard change element or a model change element and assigns a worker to perform a corresponding operation. And work to develop a schedule plan. When developing a change plan, work must be carried out to include a change plan for applications and technologies, as well as data-related change plans, so that a comprehensive change plan can be established.

The detailed step of establishing the change plan may include change impact analysis (s821), formulation (s822), change work planning (s823), and the like.

15B illustrates a data management policy establishment process according to an embodiment of the present invention.

In more detail, FIG. 15B defines a data acquisition plan necessary for achieving the company's vision and goals and a system and plan for effectively maintaining the secured data when a failure occurs in the quality management target DBMS 100. As a work, the company establishes a data management policy to secure data that meets the institution's vision and goals, and to establish a basic principle and management system that can reliably serve the acquired data in the desired form at the desired time. The purpose of the detailed management of the data management policy establishment process is to include data management principles, data quality management main processes, data management organizations, and the like.

Here, the data management principle refers to the direction of data management included in regulations, plans, and guidelines established for the effective acquisition, maintenance, and management of data, and the data quality management main process is to continuously and stably serve high quality data. It means a process that defines the annual relationship between the processes defined and defined according to the characteristics of each institution.

Means defining the people and organizations responsible for supporting and managing the data management processes defined by each agency.

By establishing a data management policy, systematic and consistent data management is possible by using it as a basis for making decisions about data.

Those skilled in the art to which the present invention pertains may refer to and / or modify this drawing 15b to infer various implementation methods for the data management policy establishment process, but the present invention is directed to all inferred It includes all implementation methods, and is not limited to the implementation method shown in FIG. 15B.

Referring to FIG. 15B according to an embodiment of the present invention, the subject of the data management policy establishment in the data management policy establishment process includes a chief information officer, a data management officer, and a user. It is done.

Here, the Chief Information Officer (CIO) is in charge of data management policy establishment and data management policy publication, and the data management officer (DA) is in charge of supporting data management policy establishment and establishing and improving related processes according to the policy. The user is responsible for review of participation in the proposal policy council.

Referring to FIG. 15b, the chief information officer (CIO) establishes a data management policy for the data quality management (s210), where the data management policy is established to achieve a company's vision and goals based on a business plan. This refers to the planning of data acquisition necessary for this purpose and the system and plan for effectively managing and maintaining the data obtained. Detailed work details define processes related to database quality, select work subjects to perform the defined processes, and establish an education system to cultivate the ability of the selected work subjects to perform the work smoothly. Etc.

In the detailed step of establishing the data management policy, when the data management policy needs to be established and changed according to changes in the environment of the business or IT, a data management policy establishment step of collecting the necessary related data and creating policy data (s211). , And / or data management to review and approve the completeness, consistency, feasibility, etc. of the policy by attending the Chief Information Officer (CIO), the relevant users, and the relevant data management officer based on the established policy. A policy review step (s212), and / or a data management policy publication step (s213) for proclaiming the confirmed data management policy, and if necessary to define and modify the data management process according to the policy change, to perform it. It is preferable to make it.

15c illustrates a data standard change process according to an embodiment of the present invention.

In more detail, FIG. 15C shows a standard word dictionary and domain dictionary, a standard term dictionary, a standard code, and a data related element standard defined in accordance with the data standardization principle when an obstacle occurs in the quality management target DBMS 100. Defining and modifying the data in the proper form, and purifying and improving the data by checking compliance with data standards, supporting the design and development of the database, and interoperability between systems through the use and reuse of company-wide data standards. , Data sharing, system integration, business process improvement, and the like to maintain data consistency and consistency through the use of common standards across the enterprise.The data standard definition process, data standard change process, and data standard evaluation process. The specific subjects of the standard word dictionary It includes standard domain dictionaries, standard term dictionaries, standard codes, and data standard elements.

Those skilled in the art will be able to infer various implementation methods for the data standard change process by referring to and / or modifying this figure 15c, but the present invention implements all the inferred implementations. It includes all the methods, and is not limited to the embodiment shown in this figure 15c.

Referring to FIG. 15C according to the embodiment of the present invention, the subject of the data standard change in the data standard change process includes a data manager (DA), a modeler, and the like.

Here, the data manager (DA) is responsible for reviewing standardization requirements, standard word dictionary and domain dictionary, code dictionary, term dictionary, data related element change, data standard registration and publication, etc., and the modeler confirms and applies the standard. It is in charge of the back.

Referring to FIG. 15c, the data management officer DA changes a data standard for the data quality control (s320), wherein the change of the data standard includes the defined data standard (word standard, domain standard, code standard, Change management work that reflects new and additional requests for data-related component standards). By modifying the standards for which changes are requested, and analyzing model changes that need to be adjusted as the standards change, the model changes are requested to maintain a standardized data model.

The detailed step of changing the data standard may include a change requirement review step (s321), and / or a standard addition and change step (s322), and / or a standard change impact evaluation step (s323), and / or a standard registration and It is preferable to include the publication step (s324) or the like.

The detailed step of changing the data standard is to first check whether the requested standard change requirement is a requirement that can be handled using a previously defined data standard, and request further change work only when it is determined that addition and change are necessary. The change requirements review step (s321), and / or the details of standard change elements are added and changed in accordance with the data standardization principle. When the change is completed, the standard addition and change step (s322) requesting the impact assessment work and the publication work based on the change, and / or the change of the standard affects an existing table or column. Modeling by identifying changed tables, attributes, and other elements that need to be changed, and the standard change impact assessment step (s323) requesting the relevant modeler for the operation, and / or publishing the changed data standard through the standard addition and change operation. It is preferable to include a standard registration and publication step (s324) and the like used in the operation and database management operations.

15d illustrates a data standard evaluation process in accordance with an embodiment of the present invention.

In detail, FIG. 15D shows a standard word dictionary and domain dictionary, a standard term dictionary, a standard code, and a data related element standard defined in accordance with the principles of data standardization when an error occurs in the DBMS 100 to be controlled. Defining and modifying the data in the proper form, and purifying and improving the data by checking compliance with data standards, supporting the design and development of the database, and interoperability between systems through the use and reuse of company-wide data standards. , Data sharing, system integration, business process improvement, and the use of common standards across the enterprise to maintain consistency and consistency of data, and to evaluate the data standard definition process and data standard change processes and data standards. Process control targets include standard word dictionary, It includes standard domain dictionaries, standard term dictionaries, standard codes, and data standard elements.

Those skilled in the art will be able to infer various implementation methods for the data standard evaluation process by referring to and / or modifying this drawing 15d, but the present invention is intended to implement all the inferred implementations. It includes all the methods, and is not limited to the embodiment shown in this figure 15d.

Referring to FIG. 15D according to an embodiment of the present invention, the subject of data evaluation in the data standard improvement process includes a data manager (DA), a modeler and a database manager (DBA).

Here, the data manager (DA) is responsible for data standards (data model mapping), data standards compliance check (data standards-concept data model standards check), change impact analysis (data standard change impact analysis), The modeler is responsible for data standards (data model mapping), data standard compliance check (data standard-logic, physical data model compliance check), change impact analysis (data model change impact analysis), and the database manager (DBA). ) Is responsible for data standards (database object mapping), data standard compliance checks (data standards-database object standard compliance checks), and change impact analysis (database structure change impact analysis).

Referring to FIG. 15D, the data manager (DA) evaluates a data standard for the data quality control (s330), wherein the data standard evaluation is in compliance with terms, domains, and code standards defined throughout the organization. This includes evaluating standards for compliance with the defined standards and data models, and performing improvements based on the analysis of cause and change impacts for non-compliant data.

The detailed step of evaluating the data standard may include a data standard evaluation step (s331), and / or a data standard compliance check step (s332), and / or a change impact analysis step (s333), and / or a data standard non-compliance cause analysis It is preferable that the step (s333), the data purification step (s334) and the like.

The detailed step of evaluating the data standard may include mapping the data standard and the data model (s331), and / or the data standard reflecting the term standard, domain standard, and naming convention standard to the data model (concept, logic, and physics). Data standard compliance check step (s332) for checking whether the data standard is compliant between data objects (data model, database object), and / or change impact analysis for analyzing the impact on the non-compliance part of the data standard in the above checking process. Analysis step (s333), and / or data standard for analyzing the cause of non-compliance by checking whether the data standard is observed for actual data values; non-compliance cause analysis step (s334); and / or the above data standard It includes a data refinement step (s335) to modify the data through a number of analysis for the data that does not comply with It is good.

15E illustrates a data model improvement process according to an embodiment of the present invention.

In more detail, FIG. 15E illustrates that when a failure occurs in the quality control target DBMS 100, a data model is maintained in the same manner as a database system structure and a work procedure that reflects the data structure changed by data requirement management in a model. The data model is intended to systematically manage to provide an optimized data service for the organization's business purpose and to construct and maintain a database. This includes conceptual data models, data reference models, logical data models, and physical data models.

Those skilled in the art will be able to infer various implementation methods for the data model improvement process by referring to and / or modifying this drawing 15e, but the present invention is intended to implement all the inferred implementations. All the methods are included, and the method is not limited to the embodiment shown in FIG. 15E.

Referring to FIG. 15E according to an embodiment of the present invention, the subject of data model improvement in the data standard definition process includes a data manager (DA), a modeler and a database manager (DBA).

Through the data model improvement process, it is possible to understand the enterprise data structure through the correlation analysis of logical and physical data models based on the conceptual data model, and the same model as the current database through the correlation analysis between the physical data model and the database. The acquisition enables maintenance and systematic management of enterprise-wide databases, and by utilizing a data reference model, a certain level of data model and high-quality data service are possible.

Here, the data manager (DA) is responsible for concept-logical data model mapping, concept-logical data model alignment analysis, etc., the modeler is responsible for o logic-physical data model mapping, logic-physical data model Align analysis, etc. The database manager (DBA) is responsible for physical data model-DB mapping, physical data model-DB analysis, and the like.

Referring to FIG. 15E, the modeler evaluates a data model for the data model improvement process (s430), wherein the data model evaluation is a task of evaluating a data model managed by the corresponding organization. Implement data model improvement for errors caused by mapping between models, logical models-between physical models, physical models-between DBs, and alignment analysis, and improve DBMS through impact analysis. .

Detailed steps for improving the data model include: concept-logical model mapping (s431), logic-physical model mapping (s432), physical model-DB mapping (s433), concept-logical model Align analysis (s434), logic-physical It is preferable to include model alignment analysis (s435), physical-DB alignment analysis (s436), and the like.

The detailed step of improving the data model is to generate structural connection information between the conceptually generated data set or management item and the logical data model, and between each object of the conceptual data model and each object between the logical data model from a data architecture perspective. Logical model mapping step of setting alignment (s431), and / or structural alignment information between physical data models based on business model data structure and the physical characteristics of the database based on the business rules Logical to set the-physical model mapping step (s432), and / or the structural alignment (alignment) between the physical data model (final design drawing) and the DBMS catalog (building) information. Most modeling tools automatically generate connection information between the physical data model and the database (s433), and / or check whether a model defined in the conceptual data model does not exist in the actual logical data model. The gap analysis work. With this analysis, the process of changing the conceptual data model or changing the logical data model is performed (s434), and / or analyzing the gap between the logical data model and the physical data model. Analyze the change from the modeler perspective to perform the change on the corresponding data model (s435), and / or analyze the gap between the physical data model and the actual DB. In this case, it is preferable to include a physics-DB alignment analysis step (s436) for analyzing whether there is a DB object that is not represented in the model.

Figure 15f illustrates a data flow improvement process in accordance with an embodiment of the present invention.

More specifically, FIG. 15f illustrates that when a failure occurs in the quality management target DBMS 100, source data (document, text, DB, etc.) are generated by handwriting, or generated through extraction, conversion, and loading and stored in a target database. It means to manage the processing, and to manage the life cycle in which the data managed by each organization is created, changed and utilized, to check the status of enterprise data and to make sure that it is utilized in an optimized form. Detailed management targets in the data flow improvement process include source work data, operational work data, analysis work data, and flow management data.

Those skilled in the art to which the present invention pertains will be able to infer various implementation methods for the data flow improvement process by referring to and / or modifying this figure 15f, but the present invention is intended to implement all the inferred implementations. All the methods are included, and the method is not limited to the embodiment shown in FIG. 15F.

Referring to FIG. 15f according to an embodiment of the present invention, the subject of the data flow improvement in the data flow improvement process includes a data manager (DA), a modeler and a database manager (DBA), and a user. do.

The data flow improvement process enables data extraction and transformation, monitoring and systematic management of data, increasing the accuracy and stability of the data and improving the reliability of the data.

Herein, the data manager DA is responsible for deriving data flow check criteria, analyzing error data, and the modeler is responsible for generating data flow check indicators and analyzing change impact, and the database manager DBA is responsible for data consistency. It is in charge of check.

Referring to FIG. 15F, the modeler evaluates the data flow for the data quality management (S520), wherein the data flow evaluation is an operation for generating the source data to evaluate the consistency of data stored and managed as target data. Data flow check criteria and indicators are established, data consistency is checked, error data is analyzed, and impact analysis results are reflected and improvement is performed.

The detailed steps of defining the data flow improvement include derivation of data flow check criteria (s521), generation of data flow check indicators (s522), data consistency check (s523), error data analysis (s524), change impact analysis (s525), It is preferable to include data purification (s526).

The detailed step of defining the data flow improvement may include a step of deriving data flow check criteria (s521) for deriving a standard to be managed through quality inspection in order to minimize data errors, and / or by the data flow check criteria above. A data flow check indicator generation step (s522) for deriving indicators for checking the consistency of the specific data flow, and / or a data consistency check step (s523) for checking the consistency by executing specific check modules according to the above indicators, And / or error data analysis step s524 for performing analysis on the error data extracted through data consistency verification, and / or analyzing the cause of the error data in the above checking process, specifically changing the data standard. Impact of changing data model, impact of changing database object It is preferable to include a change impact analysis step (s525) for analyzing the data, and / or a data purification step (s526) for modifying the data through various analysis operations for the error data that does not ensure data integrity.

Figure 15g illustrates a database improvement process according to an embodiment of the present invention.

In more detail, Figure 15g is a system to organize the operations necessary for the stable operation and management of the database required for smooth data service, if the failure occurs in the DBMS 100, the quality control target backup, security, tuning, monitoring, etc. A database management task is a system to continuously create and change a database, improve security, improve performance, and manage backups so that the database and data stored in the database can be reliably serviced without errors and corruption. A detailed management object in the database improvement process includes standard data, model data, management data, business data, and the like.

Those skilled in the art will be able to infer various implementation methods for the database improvement process by referring to and / or modifying this drawing 15g, but the present invention is directed to all implementation methods that are inferred. It includes all, and is not limited to the embodiment shown in Figure 15g.

Through the database improvement process, the database management systemization enables the user to prepare the foundation for stable and continuous business activities by accurately and reliably serving the desired data in the desired form at the desired time without any error or damage of the data.

Referring to Fig. 15g according to the embodiment of the present invention, the subject of database improvement in the database improvement process includes a data management officer (DA), a chief information officer (CIO), a database manager (DBA), and the like. It is done.

The data manager DA is responsible for change impact analysis (data standard change impact analysis), and the chief information officer (CIO) is responsible for change impact analysis (data model change impact analysis), and the database. Managers (DBAs) are responsible for database object management (object management efficiency analysis, object management inefficiency analysis) and change impact analysis (database structure change impact analysis).

Referring to FIG. 15G, the database manager (DBA) evaluates a database for the data quality management (s630), wherein the database evaluation identifies a constraint and an object type assigned to a database object to an object of a currently set database. Evaluate whether the rule is suitable to ensure optimal performance and to prevent data errors. For this purpose, after checking the constraints and object types specified for efficiency, the effect of changing constraints or object types in the database to analyze the cause of the inefficient object management type or object type and to improve the inefficiency. Analyze the diagram.

The detailed step of improving the database may include database object management efficiency check (s631), inefficiency cause analysis (s632), change impact analysis (s633), and the like.

The detailed step of improving the database includes checking database object management efficiency whether it is object management rules for checking optimal constraints and object types for objects in the currently set database to ensure optimal performance and preventing data errors (s631). , And / or if the currently configured object management type or object type exhibits inefficient performance, the inefficiency cause analysis step of analyzing the cause (s632), and / or changes the constraint or object type in the database to improve inefficiency. However, if a change of the integrated separation of the table is required, a change of the physical data model may be required, and if the domain of the object can be changed, a change impact analysis step in which a change of the data standard may be reversed may be required (s633). It is preferable to include a step and the like.

15h illustrates a data utilization management process according to an embodiment of the present invention.

More specifically, FIG. 15h shows that quality is measured and analyzed by selecting measurement target data and quality indicators in order to check whether data is utilized or to increase utilization when a failure occurs in the quality management target DBMS 100. If it does not, it means analyzing the cause and causing the person to take action. V Checking the data that is not utilized in the application to improve the DB environment and evaluating and improving the quality of the data with high business importance. In order to increase the utilization of the data, the database management process includes detailed data of high importance directly affecting the company's customers, processes, market environment, financial information, and the like.

Those skilled in the art to which the present invention pertains may refer to and / or modify this drawing 15h to infer various implementation methods for the data utilization management process, but the present invention is intended to implement all the inferred implementations. It includes all the methods, and is not limited to the embodiment shown in this figure 15h.

Analyzing and improving the cause of data deterioration by the data utilization management process has the effect of improving the quality and usability of continuous data.

Referring to FIG. 15h according to the embodiment of the present invention, the subject of the data utilization management in the data utilization management process includes a data manager (DA), a modeler, a user, and the like.

Here, the data manager (DA) is responsible for establishing core data collection and utilization measurement standards, evaluating improvement activities, etc. The modeler is responsible for measuring data utilization, analyzing utilization degradation factors, establishing improvement plans, and performing improvement activities. For example, the user is responsible for presenting data utilization opinions.

Referring to FIG. 15h, the modeler manages data utilization for data quality management (s710), wherein the data utilization management selects data to be measured and quality indicators to check whether data is used or to increase utilization. When measuring and analyzing quality does not meet the quality, the cause is analyzed to cause the person in charge to take action.

The detailed steps of the data utilization management, core data collection (s711), utilization measurement criteria establishment (s712), data utilization measurement (s713), utilization degradation factor analysis (s714), improvement measures (s715), improvement activities performed ( s716), improvement activity evaluation (s717), and the like.

The detailed step of managing data utilization includes preparing and selecting selection data to be improved, and a core data collection step (s711) for adjusting the amount of measurement data in consideration of work load and system load, and / or utilization of data. Establish metric quantitatively and set data utilization improvement targets to evaluate future improvement work (S712), and / or utilize data to perform utilization evaluation based on data utilization metrics Measurement step (s713), and / or utilization deterioration factor analysis step (s714), and / or deterioration, which derive from the perspective of generation, update, transformation, and utilization of data, the business and IT causes that caused the deterioration of data utilization. In the preparation of improvement plan by cause (s715) and / or the action plan of approved improvement plan and improvement plan derived by cause. Therefore, in the process of promoting improvement activities and / or performing improvement activities (s716), and / or evaluating improvement activities, data exceeding the measurement targets are excluded from the improvement items, or the target values are adjusted. It is desirable to include the improvement activity evaluation step (s717) that can be summarized so that it can be used for future activities.

15I illustrates a requirements management process in accordance with an embodiment of the present invention.

More specifically, FIG. 15i refers to a task of collecting, classifying, and reflecting user's requests across data and related applications and systems when a failure occurs in the quality management target DBMS 100, and requesting user's information. It aims to improve user's satisfaction and enable high-quality service by reviewing and confirming matters comprehensively, and improving and reflecting the system to meet the requirements.The detailed management subject of the database operation process is the improvement of external interface requirements and functions. Requirements, performance improvement requirements, security improvement requirements, etc.

Those skilled in the art will be able to infer various implementation methods for the requirements management process by referring to and / or modifying this figure 15i, but the present invention is directed to all implementations inferred from the above. All the methods are included and the method is not limited to the embodiment shown in FIG.

The requirement management process has the effect of increasing user satisfaction through systematic and comprehensive processing of user requirements and securing traceability of requirements.

Referring to FIG. 15I according to an embodiment of the present invention, the subject of the requirements management in the requirements management process includes a data manager (DA), a modeler, a user and a service desk.

Here, the data management officer (DA) is the requirements formalization and requirements processing type definition,

It is in charge of revision and change plan establishment through analysis of change impact, and the modeler is in charge of reviewing requirements and determining whether it can be processed, the user is in charge of change requests, and the service desk is in charge of collecting requirements. do.

Referring to FIG. 15i, the user confirms the requirements for the data quality management (s810), where the requirements check is performed to remove the user's requirements in order to eliminate and minimize the risk of business continuity and obstacles in advance. It is the work of establishing and analyzing. Analyze the impact of database changes on the basis of requirements and define application priorities based on the analysis results. After analyzing the impact and importance of the requirements, determine whether to develop a new system or change an existing one, taking into account size and timing of application.

The detailed requirements management step preferably includes a change request (s811), a request convergence (s812), a requirement review (s813), and the like.

The detailed step of managing the requirements may include a change request step (s811) for requesting a request for change through an application for change of requirements such as an external interface and a function, performance, security, etc. generated by the user using the system of the institution; and And / or a requirements gathering step (s812) that verifies that the requested change request has been collected from the user and accurately defined in accordance with the rules for making a change application, and designates a modeler to review the requirements, and / or the requested request. It is preferable to include a requirement review step (s813) for checking the data, standards, systems, etc. related to the matter to determine whether it can be processed and requesting formalization through DA if possible.

In order to manage the requirements, the user establishes a change plan (s820), where the change plan determines whether a change of an existing system needs to be a standard change element or a model change element and assigns a worker to perform the corresponding work. And work to develop a schedule plan. When developing a change plan, work must be carried out to include a change plan for applications and technologies, as well as data-related change plans, so that a comprehensive change plan can be established.

The detailed step of establishing the change plan may include change impact analysis (s821), formulation (s822), change work planning (s823), and the like.

The detailed step of establishing the change plan may include a change impact analysis step (s821) for deriving a design document, an application, a database, etc. that affect the change based on the change request details, and / or change processing through the impact analysis. The formalization step (s822), which assembles and formalizes the relevant personnel who are required, and consults with those persons to determine whether to approve the change and how to handle the change, and / or the impact assessment report to identify the relevant work area and related system details. It is preferable to include a work schedule planning step (s823) and the like based on.

Hereinafter, when a new system for the quality control target DBMS 100 is developed, a process of quality control for the quality control target DBMS 100 is described based on a database quality management framework.

Figure 16a illustrates a main process of data quality control in accordance with an embodiment of the present invention.

In more detail, when FIG. 16A illustrates a new system for the quality management target DBMS 100, data standard management, data model management, data flow management, database, and the like are established from a data management policy for operation and management of high quality data. A series of data management activities ranging from management, data utilization management, and requirements management, to the definition of data in the form most appropriate for the organizational environment of an institution or enterprise by understanding the systematic process for high quality data management. It is aimed at supporting the establishment of a series of processes such as evaluation, evaluation, and change. The main subjects of the data quality control main process are data management policy, data standard management, data model management, data flow management, and database management. , Data utilization management, requirements Including port management.

Those skilled in the art will be able to infer various implementation methods for the data quality control main process by referring to and / or modifying this figure 16a, but the present invention is inferred from all It includes all implementation methods and is not limited to the implementation method shown in FIG.

Referring to FIG. 16A according to an embodiment of the present invention, the database quality control subject is a chief information officer, a data manager, a modeler, a database manager, a user, and the like. Characterized in that comprises a.

Here, the chief information officer (CIO) is in charge of the overall data management, data management policy formulation and coordination of issues between data managers, the data management officer (DA) is the overall data change management general, enterprise data integration model management, And the development and coordination of data standards, and the modeler is responsible for coordinating and integrating data requirements and issues in the functional areas, performing data modeling based on the business requirements of the functional areas, and confirming and applying standards. The database manager (DBA) is responsible for database design, configuration management of the database and data, monitoring, tuning and security management of the database, and the user requests utilization of data and operational analysis data and additional requirements for the data. It is in charge of the back.

Referring to FIG. 16A, the chief information officer (CIO) establishes a data management policy for the data quality management (s210), where the data management policy is established to achieve a company's vision and goals based on a business plan. It is the task of defining the data acquisition plan necessary for the purpose and the system and plan for effectively managing and maintaining the acquired data. Detailed work details define processes related to database quality, select work subjects to perform the defined processes, and establish an education system to cultivate the ability of the selected work subjects to perform the work smoothly. Etc.

In the detailed step of establishing the data management policy, when the data management policy needs to be established and changed according to changes in the environment of the business or IT, a data management policy establishment step of collecting the necessary related data and creating policy data (s211). , And / or data that the chief information officer (CIO), related users, and related data managers attend, based on the established policy, and review and approve the completeness, consistency and feasibility of the policy. Reviewing the management policy step (s212), and / or proclaiming the determined data management policy, and the data management policy publication step (s213) for performing the definition and modification of the data management process according to the policy change, and the like. It is preferable to comprise.

When a new system for the quality management target DBMS 100 is developed, the data manager (DA) defines a data standard for the data quality control (s310), where the data standard definition is used by a corresponding institution. Defining standards across domains, codes, and data-related elements, including defining terminology based on the standard, collecting user standardization requirements, and defining enterprise standards for each standardization element. do.

The detailed step of defining the data standard may include standardization requirement collection step (s311), and / or standardization principle establishment step (s312), standard word dictionary definition step (s313), and / or standard domain dictionary definition step (s314). And / or standard code definition step s315, and / or standard term definition step s316, and / or data-related element standard definition step s317, and / or data standard review step s318, and / or It is preferable to include a data standard publication step (s319) or the like.

For the data quality management, the data manager DA changes the data standard (s320), wherein the data standard change is performed on the defined data standard (word standard, domain standard, code standard, data related element standard). A change management task that reflects new and additional requests for this information. By modifying the standards for which changes are requested, and analyzing model changes that need to be adjusted as the standards change, the model changes are requested to maintain a standardized data model.

The detailed step of changing the data standard may include a change requirement review step (s321), and / or a standard addition and change step (s322), and / or a standard change impact evaluation step (s323), and / or a standard registration and It is preferable to include the publication step (s324) or the like.

For the data quality management, the data management officer (DA) evaluates a data standard (s330), wherein the data standard evaluation is defined as an operation for evaluating the compliance status of terms, domains, and code standards defined by the organization. This includes checking the compliance of the standards through mapping of the standard and the data model, and improving the non-compliant data by reflecting the results of the cause and change impact analysis.

The detailed step of evaluating the data standard may include a data standard evaluation step (s331), and / or a data standard compliance check step (s332), and / or a change impact analysis step (s333), and / or a data standard non-compliance cause analysis It is preferable that the step (s333), the data purification step (s334) and the like.

For the data quality management, the modeler defines a data model (s410), wherein the data model definition is a conceptual data model, a data reference model, a logical data model, a physical data model designed through a data modeling task when developing a new system. It refers to the work required to create and maintain company-wide. If it is not created and managed previously, a separate work plan should be established to define the same data model as the schema of the database currently in operation.

The detailed step of defining the data model may include a conceptual data model definition step (s411), and / or a data reference model definition step (s412), and / or a logical data model definition step (s413), and / or a physical data model definition. It is preferable to include the step s414 and the like.

For the data quality management, the modeler changes a data model (s420), wherein the data model change is an operation of changing a data model based on a data standard and a data reference model to provide a service suitable for user requirements. When making changes, change management must be done simultaneously so that conceptual data model, logical data model and physical data model can be related. When changing the model, it is necessary to consider whether the elements defined in other areas are duplicated or changed according to the consistency of data.

The detailed step of defining the data model preferably includes a conceptual data model changing step (s421), a logical data model changing step (s422), and / or a physical data model changing step (s423). .

For the data quality management, the modeler evaluates the data model (s430), wherein the data model evaluation is an operation for evaluating the data model managed by the corresponding organization throughout the concept model-between logical models, logical models-physical Implement data model improvement for errors caused by mapping between models and physical model-to-DB mapping and alignment analysis, and improve DBMS through impact analysis.

The detailed steps for defining the data model include: concept-logical model mapping (s431), logic-physical model mapping (s432), physical model-DB mapping (s433), concept-logical model alignment analysis (s434), logic-physical It is preferable to include model alignment analysis (s435), physical-DB alignment analysis (s436), and the like.

For the data quality control, the modeler defines a data flow (s510), where the

Data flow definition is to control and manage the life cycle of data stored in the target database through manual creation, extraction, conversion, loading, and processing of source data (document, text, DB, etc.). And batch work of structured / unstructured data.

The detailed steps of defining the data flow include: data extraction (transformation) definition definition (s511), source data analysis (s512), source data extraction (transformation) design (s510), source data extraction (transformation) test (s514), Source data extraction (conversion) verification (s515), source data extraction (conversion) module reflection (s516), source data extraction (conversion) monitoring (s517) and the like is preferably made.

In order to control the data quality, the modeler evaluates the data flow (s520), wherein the data flow assessment is an operation of evaluating the consistency of data managed by generating and storing source data as target data. The error data is analyzed by checking the data integrity, and the improvement results are reflected by reflecting the impact analysis results.

The detailed steps of defining the data flow may include deriving data flow check criteria (s521), generating data flow check indicators (s522), checking data consistency (s523), analyzing error data (s524), changing impact analysis (s525), It is preferable to include data purification (s526).

For the data quality management, the modeler manages data utilization (s710), wherein the data utilization management measures and analyzes quality by selecting measurement data and quality indicators to check whether data is used or to increase utilization. When quality is not met, the cause is analyzed to cause the person in charge to take action.

The detailed steps of defining the data flow include collecting core data (s711), establishing utilization measurement standards (s712), measuring data utilization (s713), analyzing utilization degradation factors (s714), preparing improvement plans (s715), and performing improvement activities. (s716), improvement activity evaluation (s717), and the like.

The database manager (DBA) defines a database (s610) for the data quality management, wherein the database definition refers to regular and irregular work required to stably operate and maintain the database, and includes a database suitable for a data model. And backup, security, recovery, and performance management.

The detailed steps of defining the database may include creating a database (s611), defining a backup cycle and schedule (s612), performing a database backup (s613), selecting a data security target (s614), applying data security (s615), and performing data security training. (s616) and the like are preferable.

The database manager (DBA) changes the database (s620) for the data quality management, wherein the database change refers to a task of changing the database based on the changed data model according to the requirements.

The detailed step of changing the database may include database improvement (s621), data security improvement (s622), database recovery (s623), test database change (s624), operational database transfer (s625), and the like. .

The database manager (DBA) evaluates the database for the data quality management (s630), wherein the database evaluation checks the constraints and object types assigned to the database objects to the objects of the currently set database so that the corresponding rule performs the best performance. To ensure that it is suitable and to prevent errors in the data.

For this purpose, after checking the constraints and object types specified for efficiency, the effect of changing constraints or object types in the database to analyze the cause of the inefficient object management type or object type and to improve the inefficiency. Analyze the diagram.

The detailed step of evaluating the database may include database object management efficiency check (s631), inefficiency cause analysis (s632), change impact analysis (s633), and the like.

For the data quality management, the user checks the requirements (s810), where the requirements check is a task of establishing and analyzing the user's requirements in order to eliminate and minimize the risk of business continuity and obstacles in advance. Analyze the impact of database changes on the basis of requirements and define application priorities based on the analysis results. After analyzing the impact and importance of the requirements, determine whether to develop a new system or change an existing one, taking into account size and timing of application.

The detailed step of confirming the requirements is preferably made including a change request (s811), a request convergence (s812), a requirements review (s813) and the like.

In order to control the data quality, the user establishes a change plan (s820), where the change plan determines whether a change of an existing system needs to be a standard change element or a model change element and assigns a worker to perform a corresponding operation. And work to establish a schedule. When developing a change plan, work must be carried out to include a change plan for applications and technologies, as well as data-related change plans, so that a comprehensive change plan can be established.

The detailed step of establishing the change plan may include change impact analysis (s821), formulation (s822), change work planning (s823), and the like.

16b illustrates a data management policy establishment process according to an embodiment of the present invention.

In more detail, FIG. 16B illustrates a system and plan for effectively maintaining data and a data acquisition plan necessary to achieve a company's vision and goals when a new system for the quality management target DBMS 100 is developed. By defining data management policies, companies establish data management policies to secure data that meets the organization's vision and goals, and establish basic principles and management systems that can reliably serve the acquired data at desired times and in desired forms. It is aimed at establishing a data management policy, and the detailed management target of the data management policy establishment process includes data management principles, data quality management main processes, and data management organizations.

Here, the data management principle refers to the direction of data management included in regulations, plans, and guidelines established for the effective acquisition, maintenance, and management of data, and the data quality management main process is to continuously and reliably serve high quality data. It refers to a process that defines the annual relationship between the processes defined and defined in accordance with the characteristics of each institution. In addition, the data management organization means defining the people and organizations that will support and be in charge of the data management processes defined by each organization.

By establishing a data management policy, systematic and consistent data management is possible by using it as a basis for making decisions about data.

Those skilled in the art to which the present invention pertains may refer to and / or modify this drawing 16b to infer various implementation methods for the data management policy establishment process, but the present invention is directed to all inferred It includes all implementation methods and is not limited to the implementation method shown in FIG. 16B.

Referring to FIG. 16B according to an embodiment of the present invention, the subject of the data management policy establishment in the data management policy establishment process includes a chief information officer, a data management officer, and a user. It is done.

Here, the Chief Information Officer (CIO) is in charge of data management policy establishment and data management policy publication, and the data management officer (DA) is responsible for establishing and improving data management policy establishment support and related processes according to the policy. The user is in charge of participating in the proposal policy council.

Referring to FIG. 16b, the chief information officer (CIO) establishes a data management policy for the data quality management (s210), where the data management policy is established to achieve a company's vision and goals based on a business plan. It is the task of defining the data acquisition plan necessary for the purpose and the system and plan for effectively managing and maintaining the acquired data. Detailed work details define processes related to database quality, select work subjects to perform the defined processes, and establish an education system to cultivate the ability of the selected work subjects to perform the work smoothly. Etc.

In the detailed step of establishing the data management policy, when the data management policy needs to be established and changed according to changes in the environment of the business or IT, a data management policy establishment step of collecting the necessary related data and creating policy data (s211). , And / or data management to review and approve the completeness, consistency, feasibility, etc. of the policy by attending the Chief Information Officer (CIO), the relevant users, and the relevant data management officer based on the established policy. A policy review step (s212), and / or a data management policy publication step (s213) for proclaiming the confirmed data management policy, and if necessary to define and modify the data management process according to the policy change, to perform it. It is preferable to make it.

Figure 16c illustrates a data standard definition process according to an embodiment of the present invention.

In more detail, FIG. 16C illustrates a standard word dictionary and domain dictionary, standard term dictionary, standard code, data related element standard, etc. defined according to data standardization principles when a new system for the quality management target DBMS 100 is developed. Definition and change management in a form suitable for the institution, and data purification and improvement activities by checking compliance with data standards, supporting the design and development of the database, and using and reusing system data standards throughout the system. It aims to maintain consistency and consistency of data by supporting interoperability, data sharing, system integration, business process improvement, and by using common standards throughout the enterprise. The target of detailed management of the standard evaluation process is This includes word dictionaries, standard domain dictionaries, standard term dictionaries, standard codes, and data standard elements.

Those skilled in the art will be able to infer various implementation methods for the data standard definition process by referring to and / or modifying this figure 16c, but the present invention is directed to all the inferred implementations. It includes all the methods, it is not limited to the embodiment shown in Figure 16c.

Referring to FIG. 16C according to an embodiment of the present invention, the subject of the data standard definition in the data standard definition process includes a data management officer (DA), a user and a chief information officer (CIO). .

Here, the data manager (DA) is responsible for collecting enterprise standardization requirements, establishing data standardization principles, quasi-word dictionaries, domain dictionaries, code dictionaries, term dictionary definitions, and data standard publications. It is responsible for approval and the Chief Information Officer is responsible for reviewing and approving data standards.

Referring to FIG. 16c, the data management officer (DA) defines a data standard (s310) for the data quality control, wherein the data standard definition refers to terms and domains, codes, and data related elements used in the corresponding institutions. Defining standards across the enterprise includes defining principles according to the standards, collecting the user's standardization requirements, and then defining the enterprise standards for each standardization element.

The detailed step of defining the data standard may include standardization requirement collection step (s311), and / or standardization principle establishment step (s312), standard word dictionary definition step (s313), and / or standard domain dictionary definition step (s314). And / or standard code definition step (s315), and / or standard term definition step (s316), and / or data-related element standard definition step (s317), and / or data standard review step (s318), and / Or a data standard publication step s319 or the like.

The detailed step of defining the data standard is a standard requirement collection step (s311) of reviewing the standards currently used and collecting requirements for establishing enterprise data standards, and / or establishing basic principles prior to defining data standardization. By establishing a standardization principle (s312) to predefine the direction for standardization, standard word dictionary definition step (s313) to extract all the words being used in the institution through existing data models and glossaries, and / or business use A standard domain predefined step (s314) for classifying domains and assigning data types for each domain in consideration of frequency of use and physical characteristics of the data, and / or selecting codes from collected terms and selecting a code value of the current code. Based on the current code to identify the integration target according to integration requirements and integration needs, A standard code definition step (s315) for defining a code and designing a mapping with the current code, and / or forming a standard term based on the word, domain, and code standard when the word, domain, and code standard are defined, and combining words, domain classification, data type length, Standard term definition step (s316) to examine whether the application of the standard based on the code value, etc. is reasonable, and / or the subject area, entity, and attribute relationship name of the logical data model that is the object of the data related element standard. Defining data-related element standards (s317) that define naming conventions such as Subject Areas, Relationships, Database & Instances, Indices, Constraints, Tablespaces, File Names, Script Names, and so on, and / or DA-defined standards. Check word dictionaries, domain dictionaries, code dictionaries, term dictionaries, etc., and ensure that the terms are correctly defined as terms currently used by your organization. Check the processing and approval. In the case of code dictionaries, it is necessary to check whether the offer is correctly defined, to check for inaccuracies in the data standard review step (s318), and / or to deploy the confirmed data standard to be applicable to the enterprise system. It is preferable to include a data standard review step (s319) for performing training for understanding and applying the data.

Figure 16d illustrates a data standard evaluation process in accordance with an embodiment of the present invention.

In more detail, FIG. 16D illustrates a standard word dictionary and domain dictionary, standard term dictionary, standard code, data related element standard, etc. defined according to data standardization principles when a new system for the quality management target DBMS 100 is developed. Definition and change management in a form suitable for the institution, and data purification and improvement activities by checking compliance with data standards, supporting the design and development of the database, and using and reusing system data standards throughout the system. It aims to maintain consistency and consistency of data by supporting interoperability, data sharing, system integration, business process improvement, and by using common standards throughout the enterprise. The target of the detailed management of the data standard evaluation process is the standard. Word (word) comprises a dictionary, standard domain (domain) dictionary, terminology (term) in advance, the standard code, data elements such as standard.

Those skilled in the art will be able to infer various implementation methods for the data standard evaluation process by referring to and / or modifying this drawing 16d, but the present invention is intended to implement all the inferred implementations. All the methods are included, and the method is not limited to the embodiment shown in FIG. 16D.

Referring to FIG. 16D according to an embodiment of the present invention, the subject of data evaluation in the data standard improvement process includes a data manager (DA), a modeler and a database manager (DBA).

Here, the data manager (DA) is responsible for data standards (data model mapping), data standards compliance check (data standards-concept data model standards check), change impact analysis (data standard change impact analysis), The modeler is responsible for data standards (data model mapping), data standard compliance check (data standard-logic, physical data model compliance check), change impact analysis (data model change impact analysis), and the database manager (DBA). ) Is responsible for data standards (database object mapping), data standard compliance checks (data standards-database object standard compliance checks), and change impact analysis (database structure change impact analysis).

Referring to FIG. 16D, the data management officer (DA) evaluates a data standard for the data quality management (s330), wherein the data standard evaluation is in compliance with terms, domains, and code standards defined throughout the organization. This includes evaluating standards for compliance with the defined standards and data models, and performing improvements based on the analysis of cause and change impacts for non-compliant data.

The detailed step of evaluating the data standard may include a data standard evaluation step (s331), and / or a data standard compliance check step (s332), and / or a change impact analysis step (s333), and / or a data standard non-compliance cause analysis It is preferable that the step (s333), the data purification step (s334) and the like.

The detailed step of evaluating the data standard may include mapping the data standard and the data model (s331), and / or the data standard reflecting the term standard, domain standard, and naming convention standard to the data model (concept, logic, and physics). Data standard compliance check step (s332) for checking whether the data standard is compliant between data objects (data model, database object), and / or change impact analysis for analyzing the impact on the non-compliance part of the data standard in the above checking process. Analysis step (s333), and / or data standard for analyzing the cause of non-compliance by checking whether the data standard is observed for actual data values; non-compliance cause analysis step (s334); and / or the above data standard It includes a data refinement step (s335) to modify the data through a number of analysis for the data that does not comply with It is good.

16E illustrates a data model operating process according to an embodiment of the present invention.

In more detail, FIG. 16E illustrates a data model similar to a work procedure and a database system structure in which a data structure changed by data requirement management is reflected in a model when a new system for the quality management target DBMS 100 is developed. The data model is intended to provide a data service optimized for the organization's business purpose and to systematically manage to construct and maintain a database, and to detail the data model operation process. Management targets include conceptual data models, data reference models, logical data models, and physical data models.

Those skilled in the art to which the present invention pertains will be able to infer various implementation methods for the data model operation process by referring to and / or modifying this figure 16e, but the present invention is intended to implement all the inferred implementations. It includes all the methods, it is not limited to the embodiment shown in Figure 16e.

Referring to FIG. 16E according to an embodiment of the present invention, the subject of data model operation in the data standard definition process includes a data manager (DA), a modeler and a database manager (DBA).

The data model operation process enables the understanding of the enterprise data structure through the correlation analysis of logical and physical data models based on the conceptual data model, and the same model as the current database through the correlation analysis between the physical data model and the database. The acquisition enables maintenance and systematic management of enterprise-wide databases, and by utilizing a data reference model, a certain level of data model and high-quality data service are possible.

The data manager DA is responsible for defining a conceptual data model, reviewing a logical data model, defining a data reference model, changing a conceptual data model, etc. The modeler is responsible for defining a logical data model, changing a logical data model, and the like. The database manager (DBA) is responsible for defining a physical data model, changing a physical data model, and the like.

Referring to FIG. 16E, the modeler defines a data model for the data quality management (s410), wherein the data model definition is a conceptual data model, a data reference model, a logic designed through a data modeling task when developing a new system. This refers to the work required to create and maintain data models and physical data models throughout the enterprise. If it is not created and managed previously, a separate work plan should be established to define the same data model as the schema of the database currently in operation.

The detailed steps for defining the data model operation may include conceptual data model definition step s411, and / or data reference model definition step s412, and / or logical data model definition step s413, and / or physical data model. It is preferable to include the definition step (s414) and the like.

The detailed step of defining the data model operation is to define the data subject areas necessary to establish the vision of each institution, and to design the enterprise information in a non-overlapping and scalable manner rather than the detailed details, and the subject areas of the data and the core data set and data. A conceptual data model definition step (s411) for defining a relationship between sets and supporting data structural alignment between a detailed logical data model and a physical data model to be defined in the future (s411), and / or a work area or a subject area standard. A data reference model definition step (s412), which defines a data model that is reusable by displaying data sets and management items, and references a previously validated data model to increase the accuracy and reuse rate of the data model and to guarantee a certain level of design quality (s412). And / or detail all data structures of a business based on business rules If you focus on extracting the interface between other subject areas when defining the conceptual data model, you should refer to the data reference model and data standard. Based on the interface, the design work focuses on the associations in the subject area, and when the definition of the logical data model is completed, the review is conducted with the DA and the user to check whether the design is appropriate for the business requirements. A definition step (s413), and / or a physical data model definition step (s414) for performing detailed design work for optimal performance in consideration of the physical characteristics of the target database based on the logical data model and the data standard, and Model changes based on the nature of the user requirements If the change size is large (interface coordination between different subject areas, change of key entity type, change of relationship between key entity types), change of conceptual data model occurs and conceptual data When the model is changed, the conceptual data model change step (s421) in which a change of the logical data model and the physical data model is necessarily performed, and / or a small scale change without changing the conceptual data model or changing the conceptual data model (topic area) Interface adjustment, entity type change, relationship between entity types, and attribute change) are requested, when the data standard is changed, the logical data model is changed, and when the logical data model is changed, the same type is applied to other subject areas. Check for redundancy and data table by checking if dataset exists Logical data model change step (s422) for maintaining a standardized model with reference to the quasi and data reference models, and / or the details of the requested changes with reference to the logical data model and data standards, and the physical characteristics of the database. It is preferable to include a physical data model change step (s423) for performing a physical data model change operation so as to exhibit optimal performance.

16E illustrates a data model improvement process according to an embodiment of the present invention.

In more detail, FIG. 16E illustrates a work procedure for reflecting the data structure changed by the data requirement management in the model and a work procedure for maintaining the data model in the same manner as the database system structure. Its purpose is to systematically manage to provide optimized data services for the purpose and to construct and maintain a database. The detailed management targets in the data model improvement process include conceptual data models, data reference models, logical data models, and physical data. Including the model.

Those skilled in the art will be able to infer various implementation methods for the data model improvement process by referring to and / or modifying this drawing 16e, but the present invention is directed to all implementations inferred from the above. All the methods are included, and the method is not limited to the embodiment shown in FIG.

Referring to FIG. 16E according to an embodiment of the present invention, the subject of data model improvement in the data standard definition process includes a data manager (DA), a modeler and a database manager (DBA).

Through the data model improvement process, it is possible to understand the enterprise data structure through the correlation analysis of logical and physical data models based on the conceptual data model, and the same model as the current database through the correlation analysis between the physical data model and the database. The acquisition enables maintenance and systematic management of enterprise-wide databases, and by utilizing a data reference model, a certain level of data model and high-quality data service are possible.

Here, the data manager DA is responsible for concept-logical data model mapping, concept-logical data model alignment analysis, and the modeler is responsible for logical-physical data model mapping, logic-physical data model alignment analysis, and the like. It is responsible for the physical data model-DB mapping, physical data model-DB analysis.

Referring to FIG. 16E, for the data model improvement process, the modeler evaluates a data model (s430), where the data model evaluation is a task of evaluating a data model managed by the corresponding organization. Implement mapping and alignment analysis between models, logical models-between physical models, and physical models-between DBs, and improve the data model for errors, and improve the DBMS through impact analysis. .

The detailed steps for defining the data model include: concept-logical model mapping (s431), logic-physical model mapping (s432), physical model-DB mapping (s433), concept-logical model alignment analysis (s434), logic-physical It is preferable to include model alignment analysis (s435), physical-DB alignment analysis (s436), and the like.

The detailed step of defining the data model is to generate structural connection information between the conceptually generated data set or management item and the logical data model. From the data architecture point of view, each object of the conceptual data model and each object between the logical data model The conceptual connection logic between the physical data model in consideration of the physical data of the database and the model data structure of the task based on the concept-logical model mapping step (s431), and / or the business rules for establishing the alignment between them. logic to set the alignment-physical model mapping step (s432), and / or establishing structural alignment between the physical data model (final design drawing) and DBMS catalog (architecture) information (s433), And / or the model defined in the conceptual data model is not specifically defined in the actual logical data model. It analyzes the difference (gap) analysis step (s434), and / or the difference (gap) between the logical data model and the physical data model that such checking whether the model is present. Analyze the change from the modeler perspective to perform the change on the corresponding data model (s435), and / or analyze the gap between the physical data model and the actual DB. By doing so, it is preferable to include a step (s436) and the like analyzing whether there is a DB object not represented in the model.

16F illustrates a data flow management process in accordance with an embodiment of the present invention.

More specifically, FIG. 16f illustrates a target database by generating source data (document, text, DB, etc.) by handwriting, or by extracting, converting, and loading when a new system for the quality management target DBMS 100 is developed. It means to manage the data stored in the organization and to process it, and to manage the life cycle in which the data managed by each organization is created, changed, and utilized. The detailed management object in the data flow management process includes source work data, operational work data, analysis work data, flow management data, and the like.

Those skilled in the art to which the present invention pertains will be able to infer various implementation methods for the data flow management process by referring to and / or modifying this figure 16f, but the present invention is intended to implement all the inferred implementations. All the methods are included, and the method is not limited to the embodiment shown in FIG.

The data flow management process enables data extraction and transformation, monitoring of loading and systematic management to increase the accuracy and stability of the data and increase the reliability of the data.

Referring to FIG. 16f according to an embodiment of the present invention, the subject of the data flow management in the data flow management process includes a data manager (DA), a modeler and a database manager (DBA), and a user. do.

Here, the data manager (DA) is responsible for reviewing the source data extraction (transformation) requirements, approving whether the source data extraction (transformation) module is applied, monitoring the source data extraction (transformation) result, and the modeler. It is responsible for analyzing source data (tables and columns) for conversion, module design for source data extraction (transformation), source data extraction (transformation) testing, monitoring source data extraction (transformation) results, etc. (DBA) is responsible for reflecting the system of the source data extraction (transformation) module, and the user is responsible for defining source data extraction (transformation) requirements and verifying the source data extraction (transformation) result.

Referring to FIG. 16f, for the data quality management, the modeler defines a data flow (s510), where the data flow definition generates, extracts, converts, and loads original data (document, text, DB, etc.) by hand. In addition, the process of controlling and managing the life cycle of data stored in the target database through processing includes periodic irregular batching and batching of structured unstructured data.

Detailed steps for managing the data flow may include defining data extraction (transformation) requirements (s511), analyzing source data (s512), designing source data extraction (transformation) (s510), testing source data extraction (transformation) (s514), Source data extraction (conversion) verification (s515), source data extraction (conversion) module reflection (s516), source data extraction (conversion) monitoring (s517) and the like is preferably made.

The detailed step of managing the data flow defines the requirements to extract (transform) data from the requirements received from the user for business operation and load it into the database, and the DBA reviews the data policy in the enterprise architecture view when reviewing the requirements. In the step of defining data extraction (transformation) requirements (s511) that define whether and how to reflect the standard, and / or analyzing the source data, Modeler decides to extract (transform) the source data and load it into the database. For the source data analysis step (s512), which analyzes the contents of the tables and columns from the source data perspective against the determined requirements, and / or the source data extraction (transformation) design, Modeler designs the transformation and loading logic of the source data. Source data extraction (transformation) design step (s513), and / or source data extraction (change) testing Modeler is responsible for the source data extraction (transformation) test step (s514) for loading the source data into the target database in a test format according to the extraction (transformation) design, and / or for source data extraction (transformation) verification. Source data extraction (transformation) verification step (s515), and / or source data extraction (transformation) module reflection, to ensure that the requirements are accurately reflected in the target database based on the target content created in the transformation test) In order to monitor the source data extraction (transformation) module (s516), and / or source data extraction (transformation) monitoring, DBA applies the source data extraction (transformation) change that has been verified by the user to the operating environment. The source data extraction (transform) module applied to the system is periodically monitored according to the prescribed rules and the result is reported to the DA. It is preferred which comprises a source to extract data (conversion) monitoring step (s517), etc.

Figure 16g illustrates a database operating process in accordance with an embodiment of the present invention.

In more detail, when the new system for the quality management target DBMS 100 is developed, FIG. 16G illustrates a system for performing operations required to stably operate and manage a database required for smooth data service. It means operations such as monitoring, and database management work continuously performs creation and modification, security, performance improvement and backup management of the database so that the data stored in the database and the database can be reliably serviced without errors and damages. It aims to be organized in such a way that, in the database operation process, the detailed management object includes standard data, model data, management data, work data, and the like.

Those skilled in the art will be able to infer various implementation methods for the database operation process by referring to and / or modifying the drawing 16g, but the present invention provides all the implementation methods that are inferred. It includes all, and is not limited to the embodiment shown in Figure 16g.

Through the database management process, the database management system enables the user to prepare the foundation for stable and continuous business activities by accurately and stably serving the desired data in the desired form at the desired time without any error or damage of the data.

Referring to FIG. 16G according to the embodiment of the present invention, the subject of the database operation in the database operation process includes a user, a database administrator (DBA), and the like.

Here, the user is responsible for testing a change program, and the database manager (DBA) is responsible for creating a database, scheduling a backup and performing a backup, restoring, selecting and applying data security targets, applying and improving data security, and improving database performance. It is in charge of change and transfer.

Referring to FIG. 16G, the database manager (DBA) defines a database (s610) for the data quality management, where the database definition refers to regular and irregular work required to stably operate and maintain the database. Database configuration and backup suitable for data model, security, recovery, performance management, etc.

The detailed operation of the database may include creating a database (s611), defining a backup cycle and schedule (s612), performing a database backup (s613), selecting a data security target (s614), applying data security (s615), and performing data security training ( s616), etc. are preferable.

The detailed operation of the database may include a database generation step (s611) of configuring a database in consideration of the physical characteristics of the database based on a DDL statement based on a data model designed according to a business requirement, and / or data in use even if any obstacle occurs. Backup is performed by referring to a backup cycle and schedule definition step (s612) for defining a backup cycle and schedule so as to allow full recovery of the backup, and / or a schedule table for each backup cycle. The backup execution procedure checks whether the database startup status is normal, allocates a time when there is no batch operation, and performs a database backup step (s613) for performing a backup, and / or evaluates the identification and value of assets to be protected. Data security target selection step (s614) that analyzes the vulnerabilities and threat factors present in the system, and / or applies security based on the importance of each security target. Data security application step (s615) to apply comprehensive security such as security, database security, application system security, PC security, and / or data security policy established by each institution should be implemented at least once a year for all members. Data security training system to systematize high quality education through work It is preferred which comprises a (s616), etc.

Referring to FIG. 16G, the database manager (DBA) changes a database for changing the database (s620), wherein the database change is performed to change the database based on the changed data model according to the requirements.

The detailed steps of changing the database may include database performance improvement (s621), data security improvement (s622), database recovery (s623), test database change (s624), operational database transfer (s625), and the like. Do.

The detailed step of changing the database may include a performance improvement step required by a user of the institution, a database performance step (s621) of handling static and dynamic numeric requests, and / or damage to important data, Data security improvement step (s622) to improve the security device when the requirements for physical access control (suggested area, controlled area, etc.) and usage control (authentication, encryption, firewall, etc.) for tampering, theft, leakage, etc. occurs, and DDL created on the basis of the data model changed according to the requirements presented by the database recovery step (s623), and / or the requirements presented by the change request, for recovering the existing backed up data due to the overall damage to the data and / or errors due to obstacles, etc. Based on the statement, the test database considering the physical characteristics of the database has the same form as the modified data model. A test database change step to change (s624), and / or a unit test to check the problem with the application based on the changes made in the test database, an integration test to test the interface with other applications, and a user test to confirm the user's satisfaction. If the stability and accuracy is secured after performing such as, it is preferable to include the operation database transfer step (s625), etc. reflecting the change history in the operation database.

16h illustrates a data utilization management process according to an embodiment of the present invention.

In more detail, Figure 16h shows that when a new system for the quality management target DBMS 100 is developed, the quality of the data is measured and analyzed by selecting the measurement target data and quality indicators in order to check whether data is used or to increase the utilization. If the quality is not met, it means analyzing the cause and causing the person to take action. V Checking the data that is not utilized by the application to improve the DB environment and evaluating the quality of the data that is of high business importance. The purpose of the improvement is to increase the utilization of data, and the database management process includes detailed data that directly affects the company's customers, processes, market environment, financial information, and the like.

Those skilled in the art to which the present invention pertains will be able to infer various implementation methods for the data utilization management process by referring to and / or modifying the drawing 16h, but the present invention provides all the inferred implementations. All the methods are included and the method is not limited to the embodiment shown in FIG. 16H.

Analyzing and improving the cause of data deterioration by the data utilization management process has the effect of improving the quality and usability of continuous data.

Referring to FIG. 16h according to the embodiment of the present invention, the subject of the data utilization management in the data utilization management process includes a data manager (DA), a modeler, a user, and the like.

Here, the data manager (DA) is responsible for establishing core data collection and utilization measurement standards, evaluating improvement activities, etc. The modeler is responsible for measuring data utilization, analyzing utilization degradation factors, establishing improvement plans, and performing improvement activities. For example, the user is responsible for presenting data utilization opinions.

Referring to FIG. 16h, the modeler performs data utilization management for data quality management (s710), wherein the data utilization management selects data to be measured and quality indicators to check whether data is used or to increase utilization. When measuring and analyzing quality does not meet the quality, the cause is analyzed to cause the person in charge to take action.

The detailed steps of the data utilization management, core data collection (s711), utilization measurement criteria establishment (s712), data utilization measurement (s713), utilization degradation factor analysis (s714), improvement measures (s715), improvement activities performed ( s716), improvement activity evaluation (s717), and the like.

The detailed step of managing data utilization includes preparing and selecting selection data to be improved, and a core data collection step (s711) for adjusting the amount of measurement data in consideration of work load and system load, and / or utilization of data. Establish metric quantitatively and set data utilization improvement targets to evaluate future improvement work (S712), and / or utilize data to perform utilization evaluation based on data utilization metrics Measurement step (s713), and / or utilization deterioration factor analysis step (s714), and / or deterioration, which derive from the perspective of generation, update, transformation, and utilization of data, the business and IT causes that caused the deterioration of data utilization. According to the steps for preparing improvement plans for each cause (s715), and / or the action plan of the approved improvement plans and the improvement plans derived for each cause. Therefore, in the process of promoting improvement activities and / or performing improvement activities (s716), and / or evaluating improvement activities, data exceeding the measurement targets are excluded from the improvement items, or the target values are adjusted. It is desirable to include the improvement activity evaluation step (s717) that can be summarized so that it can be used for future activities.

16I illustrates a requirements management process in accordance with an embodiment of the present invention.

More specifically, FIG. 16i refers to a task of collecting, classifying, and reflecting user's requests across related applications and systems, including data, when a new system for the quality management target DBMS 100 is developed. It aims to improve user satisfaction and enable high-quality service by comprehensively reviewing and confirming the information requirements of the company, and improving and reflecting the system to meet the requirements. This includes the functional improvement requirements, performance improvement requirements and security improvement requirements.

Those skilled in the art will be able to infer various implementation methods for the requirements management process by referring to and / or modifying this figure 16i, but the present invention is directed to all implementations inferred from the above. All the methods are included and the method is not limited to the embodiment shown in FIG.

The requirement management process has the effect of increasing user satisfaction through systematic and comprehensive processing of user requirements and securing traceability of requirements.

Referring to FIG. 16i in accordance with an embodiment of the present invention, the subject of the requirements management in the requirements management process includes a data manager (DA), a modeler, a user and a service desk.

Here, the data manager (DA) is responsible for formalizing the reviewed requirements, defining the requirements processing type, and modifying and establishing a change plan through analysis of the impact of change, and the modeler determines whether the requirements can be reviewed and processed. The user is in charge of change requests and the service desk is responsible for collecting requirements.

Referring to FIG. 16i, the user checks the requirements for the data quality management (s810), where the requirements check is performed to remove the user's requirements in order to eliminate and minimize the risk of business continuity and obstacles in advance. It is the work of establishing and analyzing. Analyze the impact of database changes on the basis of requirements and define application priorities based on the analysis results. After analyzing the impact and importance of the requirements, determine whether to develop a new system or change an existing one, taking into account size and timing of application.

The detailed requirements management step preferably includes a change request (s811), a request convergence (s812), a requirement review (s813), and the like.

The detailed step of managing the requirements may include a change request step (s811) for requesting a request for change through an application for change of requirements such as an external interface and a function, performance, security, etc. generated by the user using the system of the institution; and And / or the requirements convergence step (s812) to ensure that the requested change request has been collected from the user and accurately defined in accordance with the rules for making a change application, and to designate a modeler to review the requirements, and / or the requested It is preferable to include a requirements review step (s813) for checking the data, standards, systems, etc. related to the requirements to determine whether they can be processed and requesting formalization through DA if possible.

In order to manage the requirements, the user establishes a change plan (s820), where the change plan determines whether a change of an existing system needs to be a standard change element or a model change element and assigns a worker to perform the corresponding work. And work to develop a schedule plan. When developing a change plan, work must be carried out to include a change plan for applications and technologies, as well as data-related change plans, so that a comprehensive change plan can be established.

The detailed step of establishing the change plan may include change impact analysis (s821), formulation (s822), change work planning (s823), and the like.

The detailed step of establishing the change plan may include a change impact analysis step (s821) for deriving a design document, an application, a database, etc. that affect the change based on the change request details, and / or change processing through the impact analysis. The formalization step (s822), which assembles and formalizes the relevant personnel who are required, and consults with those persons to determine whether to approve the change and how to handle the change, and / or the impact assessment report to identify the relevant work area and related system details. It is desirable to include a work schedule planning step (s823) based on the above.

According to the present invention, there is an advantage of managing a high quality database in a short time and at a low cost by managing the quality of the database based on the database quality management framework in which database quality management is performed throughout the enterprise.

According to the present invention, by operating the database quality management based on the enterprise-wide framework, step by step to prevent mistakes and errors that can occur in the database quality management process, each quality control subject included in the framework complement each other Thus, there is an advantage of maintaining the database quality at high quality.

Claims (5)

Data including at least one or more standard data, model data, management data, and business data; and conceptual data model information, data reference model information, logical data model information, physical data model information, database information, and users corresponding to the model data. A database with view information; A data manager module for managing standard data and a conceptual data model (or data reference model) corresponding to the database according to the quality management policy according to the data standard management process (or a requirements management process); A modeler module configured to manage model data and logical data models corresponding to the database according to the quality management policy according to the data model management process (or data flow management process); A database manager module for managing management data and a physical data model corresponding to the database according to the quality management policy according to the database management process; And And a user module for managing business data and user views corresponding to the database according to the quality management policy according to the data utilization management process. delete delete delete delete

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