CN103473375A - Data cleaning method and data cleaning system - Google Patents
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Abstract
The invention provides a data cleaning method and a data cleaning system. The data cleaning system comprises a processor. The data cleaning method comprises the following steps of cleaning domain data from different systems according to a preset rule, and adjusting the preset rule according to a cleaning result. The data cleaning method and the data cleaning system provided by the invention have the advantages that by the technical scheme, the domain data is cleaned from different data sources so as to meet the requirement of a main database of the data cleaning system and lay a foundation for data classifying and comparison in the next step and merging to recognize different data representing the same object.
Description
Technical field
The present invention relates to computer realm, in particular to a kind of Data clean system and a kind of Data Cleaning Method.
Background technology
China's medical information is polymorphic and deposits and gradual perfection at present, and final target reaches the medical information socialization.In medical system, each system is separate, such as door emergency treatment system, be in hospital, Physical Examination System, image center etc., the patient information data demand of part system is low, typing is imperfect.Each operation system standard is inconsistent, service fields is inconsistent or language performance difference, thereby causes patient information there is no association, and between system, information is independent.Patient data only has the part field effective, can not carry out the uniqueness confirmation to the patient, the disappearance sign.Between system, platform is inconsistent, and data standard is inconsistent, and causing alternately can not be unimpeded.
Data cleansing is the first stage of carrying out Data Comparison, the credible merging of data, forming the key of unified Main index of patients, is that Main index of patients is processed the core formed.Therefore, need a kind of data cleansing scheme, different-format, the different data of expressing can be unified into and meet the data that predetermined format requires, make data normalization, be convenient to follow-up data and process, make to link up between system smooth and easy.
Summary of the invention
The present invention just is being based on the problems referred to above, has proposed a kind of data cleansing scheme, different-format, the different data of expressing can be unified into and meet the data that predetermined format requires, and makes data normalization.Be convenient to follow-up data and process, make to link up between system smooth and easy.
In view of this, according to an aspect of the present invention, proposed a kind of Data clean system, having comprised: processor, clean the numeric field data from different system according to preset rules, and adjust described preset rules according to wash result.
The form of the numeric field data in different mirror image servers is all different, likely that field is different, likely that expression way is different, it is likely the field value mistake, it is invalid that this Data clean system can identify, and undesirable data can be cleaned the numeric field data from different system, realize data normalization, be convenient to follow-up association and calculate.
In technique scheme, preferred, described processor reads the field value of every record in described numeric field data, by meeting pre-conditioned field value, is not replaced as preset value or null value or deletes described field value.
Because each data recording has all comprised one or more fields, therefore, when data are cleaned, can comprise the cleaning of field level, for example, for the time field, different systems means that mode is different, the time of these different table modes need be carried out samely, according to the form of the time field of the master data base of Data clean system, is unified.
In technique scheme, preferably, described processor, also for reading one by one the record of described numeric field data, is that the fields match that lacks field value goes out described field value according to the incidence relation between field in described record, and described field value is filled to respective field.
Although data recording has comprised a plurality of fields, but likely some field lacks key value, can identify the incidence relation between field in data recording, derive the respective field value of the field that lacks key value based on this incidence relation, thereby complete coupling and the filling of record.
In technique scheme, preferred, described processor can comprise: computing unit, for the weighted value according to each field in every record of described numeric field data, calculate total weighted value of respective record, and delete the record that total weighted value is less than or equal to threshold value.The weight that the I.D. field for example is set is 50% to the maximum, the weight that name is set is 20%, the weight minimum 5% of address field, and it is 5% that threshold value is set, while supposing to have the character value of a record only to comprise the address field, the weighted value that calculates this record is 5%, and the weighted value of this record is less than or equal to threshold value, therefore delete this record.In technique scheme, preferably, described processor is also for identifying a plurality of numeric field datas that belong to same territory, and the described a plurality of numeric field datas under more same territory, when comparing the discrepant field of tool, according to the discrepant field of the described tool of data relationship correction in the territory in described same territory.
Some the time, even if in data recording the field value of all fields all filled and expression way also correct, but in different systems, corresponding field value is different, in order to determine which field value is correct, need to there is according to data relationship correction in Xia territory, same territory the field of field value difference.For example, the system under same territory comprises public security system, market system and hospital system, and when difference appears in data recording, data recording that can public security system is as the criterion, and revises the numeric field data of other system, to guarantee the accuracy of data as far as possible.
According to a further aspect in the invention, also proposed a kind of Data Cleaning Method, having comprised: cleaned the numeric field data from different system according to preset rules, and adjust described preset rules according to wash result.
The form of the numeric field data in different mirror image servers is all different, likely that field is different, likely that expression way is different, it is likely the field value mistake, it is invalid that this Data clean system can identify, and undesirable data can be cleaned the numeric field data from different mirror image servers, realize data normalization, be convenient to follow-up association and calculate.
In technique scheme, preferred, the concrete steps of cleaning described numeric field data comprise: read the field value of every record in described numeric field data, by meeting pre-conditioned field value, be not replaced as preset value or null value.
Because each data recording has all comprised one or more fields, therefore, when data are cleaned, can comprise the cleaning of field level, for example, for the time field, different systems means that mode is different, the time of these different table modes need be carried out samely, according to the form of the time field of the master data base of Data clean system, is unified.
In technique scheme, preferably, the concrete steps of cleaning described numeric field data also comprise: read one by one the record in described numeric field data, be that the fields match that lacks field value goes out described field value according to the incidence relation between field in described record, and described field value is filled to respective field.
Although data recording has comprised a plurality of fields, but likely some field lacks key value, can identify the incidence relation between field in data recording, derive the respective field value of the field that lacks key value based on this incidence relation, thereby complete coupling and the filling of record.
In technique scheme, preferred, the concrete steps of cleaning described numeric field data can also comprise: the weighted value according to each field in every record in described numeric field data, calculate total weighted value of respective record, and delete the record that total weighted value is less than or equal to threshold value.
In technique scheme, preferred, the concrete steps of cleaning described numeric field data also comprise: identify a plurality of numeric field datas that belong to same territory, and the described a plurality of numeric field datas under more same territory; When comparing the discrepant field of tool, according to the discrepant field of the described tool of data relationship correction in the territory in described same territory.
Some the time, even if in data recording the field value of all fields all filled and expression way also correct, but in different systems, corresponding field value is different, in order to determine which field value is correct, need to there is according to data relationship correction in Xia territory, same territory the field of field value difference.For example, the system under same territory comprises public security system, market system and hospital system, and when difference appears in data recording, data recording that can public security system is as the criterion, and revises the numeric field data of other system, to guarantee the accuracy of data as far as possible.
Because data layout between different system is widely different, therefore need to be cleaned the data from different system, to meet standardized format, think that associated calculating prepare, so that link up more smooth and easy between system.The cleaning of data comprises cleaning, the cleaning of record level and the system-level cleaning of field level.It is mainly against regulation, invalid being replaced field value that field level is cleaned, and then the data layout that does not meet the master data base standard is changed.It is mainly mate and fill incorrect field and field value according to the incidence relation between field in record that record level is cleaned.System-level cleaning is that the master data under same territory is compared, and unnecessary or incorrect field is revised by data relationship in territory, thereby completed the cleaning process of data, and the data after also making to clean are also more accurate when meeting standard format.
The accompanying drawing explanation
Fig. 1 shows the block diagram of Data clean system according to an embodiment of the invention;
Fig. 2 shows the schematic diagram of data cleansing principle according to an embodiment of the invention;
Fig. 3 shows the process flow diagram of Data Cleaning Method according to an embodiment of the invention;
Fig. 4 shows the process flow diagram of Data Cleaning Method according to another embodiment of the present invention.
Embodiment
In order more clearly to understand above-mentioned purpose of the present invention, feature and advantage, below in conjunction with the drawings and specific embodiments, the present invention is further described in detail.It should be noted that, in the situation that do not conflict, the application's embodiment and the feature in embodiment can combine mutually.
A lot of details have been set forth in the following description so that fully understand the present invention; but; the present invention can also adopt other to be different from other modes described here and implement, and therefore, protection scope of the present invention is not subject to the restriction of following public specific embodiment.
Fig. 1 shows the block diagram of Data clean system according to an embodiment of the invention.
As shown in Figure 1, Data clean system 100 according to an embodiment of the invention, comprising: processor 102, clean the numeric field data from different system according to preset rules, and adjust described preset rules according to wash result.
The form of the numeric field data in different mirror image servers is all different, likely that field is different, likely that expression way is different, it is likely the field value mistake, it is invalid that this Data clean system can identify, and undesirable data can be cleaned the numeric field data from different mirror image servers, realize data normalization, be convenient to follow-up association and calculate.
In technique scheme, preferred, described processor 102 reads the field value of described numeric field data, by meeting pre-conditioned field value, is not replaced as preset value or null value or deletes described field value.
Because each data recording has all comprised one or more fields, therefore, when data are cleaned, can comprise the cleaning of field level, for example, for the time field, different systems means that mode is different, the time of these different table modes need be carried out samely, according to the form of the time field of the master data base of Data clean system, is unified.
In technique scheme, preferably, described processor 102, also for reading one by one the record of described numeric field data, is that the fields match that lacks field value goes out described field value according to the incidence relation between field in described record, and described field value is filled to respective field.
Although data recording has comprised a plurality of fields, but likely some field lacks key value, can identify the incidence relation between field in data recording, derive the respective field value of the field that lacks key value based on this incidence relation, thereby complete coupling and the filling of record.
In technique scheme, preferably, described processor 102 can comprise: computing unit 1022, for the weighted value according to each field in every record of described numeric field data, calculate total weighted value of respective record, delete the record that total weighted value is less than or equal to threshold value.The weight that the I.D. field for example is set is 50% to the maximum, the weight that name is set is 20%, the weight minimum 5% of address field, and it is 5% that threshold value is set, while supposing to have the character value of a record only to comprise the address field, the weighted value that calculates this record is 5%, and the weighted value of this record is less than or equal to threshold value, therefore delete this record.
In technique scheme, preferably, described processor 102 is also for identifying a plurality of numeric field datas that belong to same territory, and the described a plurality of numeric field datas under more same territory, when comparing the discrepant field of tool, according to the discrepant field of the described tool of data relationship correction in the territory in described same territory.
Some the time, even if in data recording the field value of all fields all filled and expression way also correct, but in different systems, corresponding field value is different, in order to determine which field value is correct, need to there is according to data relationship correction in Xia territory, same territory the field of field value difference.For example, the system under same territory comprises public security system, market system and hospital system, and when difference appears in data recording, data recording that can public security system is as the criterion, and revises the numeric field data of other system, to guarantee the accuracy of data as far as possible.
Fig. 2 shows the schematic diagram of data cleansing principle according to an embodiment of the invention.
As shown in Figure 2, the numeric field data that Data clean system 100 receives from different mirror image servers 202, although should be appreciated that in figure and mean different mirror image servers with identical label, be actually different mirror image servers, for example clinic system, Physical Examination System and the system of being in hospital.Data clean system 100 is cleaned these numeric field datas according to the form of the master data base of book server, to realize the standardization of data, obtains standardized data.When cleaning, can be divided into field level and clean, record level cleaning and system-level cleaning.
Fig. 3 shows the process flow diagram of Data Cleaning Method according to an embodiment of the invention.
As shown in Figure 3, Data Cleaning Method according to an embodiment of the invention can comprise the following steps: step 302, and clean the numeric field data from different system according to preset rules, and adjust described preset rules according to wash result.
The form of the numeric field data in different mirror image servers is all different, likely that field is different, likely that expression way is different, it is likely the field value mistake, it is invalid that this Data clean system can identify, and undesirable data can be cleaned the numeric field data from different mirror image servers, realize data normalization, be convenient to follow-up association and calculate.
In technique scheme, preferred, the concrete steps of cleaning described numeric field data comprise: read the field value of every record in described numeric field data, by meeting pre-conditioned field value, be not replaced as preset value or null value.
Because each data recording has all comprised one or more fields, therefore, when data are cleaned, can comprise the cleaning of field level, for example, for the time field, different systems means that mode is different, the time of these different table modes need be carried out samely, according to the form of the time field of the master data base of Data clean system, is unified.
In technique scheme, preferably, the concrete steps of cleaning described numeric field data also comprise: read one by one the record in described numeric field data, be that the fields match that lacks field value goes out described field value according to the incidence relation between field in described record, and described field value is filled to respective field.
Although data recording has comprised a plurality of fields, but likely some field lacks key value, can identify the incidence relation between field in data recording, derive the respective field value of the field that lacks key value based on this incidence relation, thereby complete coupling and the filling of record.
In technique scheme, preferred, the concrete steps of cleaning described numeric field data also comprise: the weighted value according to each field in every record in described numeric field data, calculate total weighted value of respective record, and delete the record that total weighted value is less than or equal to threshold value.
In technique scheme, preferred, the concrete steps of cleaning described numeric field data also comprise: identify a plurality of numeric field datas that belong to same territory, and the described a plurality of numeric field datas under more same territory; When comparing the discrepant field of tool, according to the discrepant field of the described tool of data relationship correction in the territory in described same territory.
Some the time, even if in data recording the field value of all fields all filled and expression way also correct, but in different systems, corresponding field value is different, in order to determine which field value is correct, need to there is according to data relationship correction in Xia territory, same territory the field of field value difference.For example, the system under same territory comprises public security system, market system and hospital system, and when difference appears in data recording, data recording that can public security system is as the criterion, and revises the numeric field data of other system, to guarantee the accuracy of data as far as possible.
Fig. 4 shows the process flow diagram of Data Cleaning Method according to another embodiment of the present invention.
As shown in Figure 4, in step 402, receive the numeric field data from different mirror image servers; In step 404, read the field value of numeric field data, be not replaced as preset value or null value by meeting pre-conditioned field value.Be provided with rule base in Data clean system, according to different data cases, corresponding rule is set, for example in the Data clean system master data base, the expression way of time is 2012-12-12, and the time expression way of other numeric field datas is on Dec 12nd, 2012 or 2012.12.12, the time data of these these forms can be unified into to 2012-12-12 so.Again for example, in master data base, between the word of name, there is no space, but there is space between the word of the name of numeric field data, these spaces can be deleted so, conform to the form of name in master data base.Again for example, in master data base, 1 means the sex man, and 2 mean the sex female, and, in other regional data bases, M means the man, and W means the female, therefore the sex form of numeric field data also need to be unified into to the sex form in master data base.This cleaning process is called field level and cleans.
In step 406, judge whether the field value of numeric field data has vacant position, if having, enter step 408, otherwise enter step 410.
In step 408, if the corresponding field value of certain fields default in data, the incidence relation between identification field, derive corresponding field value, and filled.
For example numeric field data comprises birth address field, I.D. field, former bit digital that the incidence relation of address field and I.D. field is ID (identity number) card No. are relevant with the birth address, if the disappearance of the number relevant for the birth address of I.D., can find out corresponding Code Number according to the field value of birth address field so, this Code Number is filled in the number lacked in I.D., so just, make the identity data record more perfect, more effectively, with more accurate, such processing procedure is called the record level and cleans.
In step 410, whether judge between different numeric field datas and if having, to enter step 412 by the discrepant character of tool, otherwise, finish this flow process.
In step 412, according to the discrepant field of data relationship correction tool in the territory in same territory.For example the ID (identity number) card No. of the ID (identity number) card No. of the user a of system A and the user a in system B is different, supposing the system A is hospital system, system B is public security bureau's system, in territory, data relationship is the weight that the weight of the data of public security bureau's system is greater than the data of hospital system, data that so can system B are as the criterion the more data of positive system A, make data more accurate.This cleaning process is called system-level cleaning.
More than be described with reference to the accompanying drawings technical scheme of the present invention, because data layout between different system is widely different, therefore need to be cleaned the data from different system, to meet standardized format, think that associated calculating prepare, so that link up more smooth and easy between system.The cleaning of data comprises cleaning, the cleaning of record level and the system-level cleaning of field level.It is mainly against regulation, invalid being replaced field value that field level is cleaned, and then the data layout that does not meet the master data base standard is changed.It is mainly mate and fill incorrect field and field value according to the incidence relation between field in record that record level is cleaned.System-level cleaning is that the master data under same territory is compared, and unnecessary or incorrect field is revised by data relationship in territory, thereby completed the cleaning process of data, and the data after also making to clean are also more accurate when meeting standard format.
In the present invention, term " a plurality of " refers to two or more, unless clear and definite restriction separately arranged.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any modification of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.
Claims (10)
1. a Data clean system, is characterized in that, comprising:
Processor, clean the numeric field data from different system according to preset rules, and adjust described preset rules according to wash result.
2. Data clean system according to claim 1, is characterized in that, described processor reads the field value of every record in described numeric field data, by meeting pre-conditioned field value, is not replaced as preset value or null value or deletes described field value.
3. Data clean system according to claim 2, it is characterized in that, described processor is also for reading one by one the record of described numeric field data, be that the fields match that lacks field value goes out described field value according to the incidence relation between field in described record, and described field value is filled to respective field.
4. Data clean system according to claim 2, is characterized in that, described processor comprises:
Computing unit, for the weighted value according to each field in every record of described numeric field data, calculate total weighted value of respective record, deletes the record that total weighted value is less than or equal to threshold value.
5. according to the described Data clean system of any one in claim 2 to 4, it is characterized in that, described processor is also for identifying a plurality of numeric field datas that belong to same territory, and the described a plurality of numeric field datas under more same territory, when comparing the discrepant field of tool, according to the discrepant field of the described tool of data relationship correction in the territory in described same territory.
6. a Data Cleaning Method, is characterized in that, comprising:
Clean the numeric field data from different system according to preset rules, and adjust described preset rules according to wash result.
7. Data Cleaning Method according to claim 6, is characterized in that, the concrete steps of cleaning described numeric field data comprise:
Read the field value of every record in described numeric field data, by meeting pre-conditioned field value, be not replaced as preset value or null value.
8. Data Cleaning Method according to claim 7, is characterized in that, the concrete steps of cleaning described numeric field data also comprise:
Read one by one the record in described numeric field data, be that the fields match that lacks field value goes out described field value according to the incidence relation between field in described record, and described field value is filled to respective field.
9. Data Cleaning Method according to claim 7, is characterized in that, the concrete steps of cleaning described numeric field data also comprise:
Weighted value according to each field in every record in described numeric field data, calculate total weighted value of respective record, and delete the record that total weighted value is less than or equal to threshold value.
10. according to the described Data Cleaning Method of any one in claim 7 to 9, it is characterized in that, the concrete steps of cleaning described numeric field data also comprise:
Identify a plurality of numeric field datas that belong to same territory, and the described a plurality of numeric field datas under more same territory;
When comparing the discrepant field of tool, according to the discrepant field of the described tool of data relationship correction in the territory in described same territory.
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