CHAPTER 5: DATABASE CONNECTIVITY AND WEB TECHNOLOGIES

DATABASE CONNECTIVITY - mechanisms through which application programs connect and communicate
with data repositories.
• Database Middleware – interface between the app program and database
• Data Repository – data management app stores data generated by app program
• Universal Data Access – collection of tech used to access and manage data source
DATABASE INTERNET CONNETIVITY – ability of database to connect to internet for accessing data and
synchronizing data between databases.
SQL DATA SERVICES – cloud-based data storage and management services provided by Microsoft.
WEB TO DATABASE MIDDLEWARE – web server is the main hub thru which internet services is accessed.
ODBC ARCHITECTURE – provides a standardized way for applications to access different databases.

CHAPTER 6: DATA ADMINISTRATION AND SECURITY

DATA INFORMATION DECISION MAKING CYCLE –
• Data: Raw facts and figures.
• Information: Processed data that provides meaning.
• Decision Making: Using information to make choices or take action.

ROLES OF DATABASE – support managerial decision-making at all levels

• Interpretation and presentation of data
• Distribution of data and information
• Preservation and monitoring of data
• Control over data duplication and use
CASE TOOLS AND COMPONENTS – Computer-Aided Systems Engineering
• FRONT CASE – gui
• BACK END – coding
CASE TOOLS

• Graphic design
• Produce structured diagrams (DFDs, ERDs, class diagrams, object diagrams)
• Screen painters and report generators
• Produce the information system’s input and output formats (end-user interface)
• Integrated repository
• Stores and cross-references the system design data; includes a comprehensive data dictionary
• Analysis segment
• Provide a fully automated check on system consistency, syntax, and completeness
• Program documentation generator
MANAGE USERS AND ESTABLISHING SECURITY –
• User: uniquely identifiable object
• Allows a given person to log on to the database
• Role: a named collection of database access privileges
• Authorizes a user to connect to the database and use system resources
• Profile: name collection of settings
• Controls how much of a resource a given user can use
DATABASE SECURITY – use of DBMS features to comply with security measures.

• Authorization management:
• User access management
• View definition
• DBMS access control
• DBMS usage monitoring

CHAPTER 7: BIG DATA ANALYTICS AND NoSQL

BIG DATA CHARACTERISTICS:
• Volume: Refers to the sheer amount of data, often too large to handle with traditional methods.
• SCALING UP – keep the same number but migrating to a larger space
• SCALING OUT – spreads out across several servers
• Variety: Denotes the diversity of data types and sources, including structured, semi-structured, and
unstructured data.
• STRUCTURED DATA – fits in predefined data model
• UNSTRUCTURED DATA – not organized to fit
• SEMI UNSTRUCTURED DATA – combined elements of both
• Velocity: Indicates the speed at which data is generated and must be processed, often in real-time.
• STREAM PROCESSING – focuses on input processing, analysis of data streams
• FEEDBACK LOOP PROCESSING – analysis of data to produce actionable results
MAP REDUCE – framework use to process large data sets
• Map function takes a collection of data and sorts and filters it into a set of key-value pairs
• Mapper program performs the map function
• Reduce summaries results of map function to produce a single result
• Reducer program performs the reduce function
NoSQL Categories – Name given to non-relational database technologies developed to address Big Data
challenges

• Key-value (KV) databases store data as a collection of key-value pairs organized as buckets which are
the equivalent of tables
• Document databases store data in key-value pairs in which the value components are tag-encoded
documents grouped into logical groups called collections
• Column-oriented databases refer to two technologies:
• Column-centric storage: data stored in blocks that hold data from a single column across many
rows
• Row-centric storage: data stored in a block that holds data from all columns of a given set of
rows
• Graph databases store data on relationship-rich data as a collection of nodes and edges
• Properties are the attributes of a node or edge of interest to a user
• Traversal is a query in a graph database
DATA ANALYSIS - Subset of business intelligence (BI) functionality that encompasses mathematical,
statistical, and modeling techniques used to extract knowledge from data
• Explanatory analytics focuses on discovering and explaining data characteristics based on existing data
• Predictive analytics focuses on predicting future data outcomes with a high degree of accuracy
DATA MINING - The process of discovering patterns, correlations, or insights from large datasets.
• Guided – end-user decides techniques to apply to data
• Automated – end-user sets up the tool to run automatically and the data mining tool applies multiple
techniques to significant relationships
PREDICTIVE ANALYSIS - It involves applying statistical algorithms and machine learning techniques to
make predictions based on patterns found in data.
HADOOP - De facto standard for most Big Data storage and Processing, Java-based framework for distributing
and processing very large data sets across clusters of computers
• Hadoop Distributed File System (HDFS): low-level distributed file processing system that can be used
directly for data storage
• MapReduce: programming model that supports processing large data sets
NEW SQL DATABASES - Database model that attempts to provide ACID- compliant transactions across a
highly distributed infrastructure