METHOD AND SYSTEM FOR ANALYSIS OF A SYSTEM FOR MATCHING DATA RECORDS

• US 20090089630A1
• Filed: 09/26/2008
• Published: 04/02/2009
• Est. Priority Date: 09/28/2007
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: Initiate Systems, Inc. (International Business Machines Corporation)
• Inventors: Goldenberg, Glenn, Schumacher, Scott, Woods, Jason
• Granted Patent: US 8,799,282 B2
• Time in Patent Office: Days
• US Class Current: 714/704
• CPC Class Codes: G06F 11/0769 Readable error formats, e.g. cross-platform generic formats, human understandable formats
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06F 16/2462 Approximate or statistical queries

Abstract

Embodiments disclosed herein provide a system and method for analyzing an identity hub. Particularly, a user can connect to the identity hub, load an initial set of data records, create and/or edit an identity hub configuration locally, analyze and/or validate the configuration via a set of analysis tools, including an entity analysis tool, a data analysis tool, a bucket analysis tool, and a linkage analysis tool, and remotely deploy the validated configuration to an identity hub instance. In some embodiments, through a graphical user interface, these analysis tools enable the user to analyze and modify the configuration of the identity hub in real time while the identity hub is operating to ensure data quality and enhance system performance.

Claims

1. A method for analyzing a system for matching data records, comprising:

utilizing an initial set of data records to produce a configuration of said system;

analyzing buckets created based on said initial set of data records or a subset thereof according to a bucketing strategy associated with said configuration of said system;

analyzing an effect of said buckets on performance of said system; and

changing said bucketing strategy accordingly.

2. The method of claim 1, wherein said changing said bucketing strategy further comprises editing an algorithm utilized in creating said buckets or changing one or more parameter values associated with said algorithm.

3. The method of claim 2, wherein said algorithm is associated with an entity type.

4. The method of claim 3, further comprising analyzing entities categorized as having said entity type in said system.

5. The method of claim 4, wherein said analyzing said entities further comprises analyzing an entity size distribution, analyzing said entities by size, analyzing said entities by composition, analyzing a score distribution associated with said entities, analyzing member comparisons associated with said entities, or a combination thereof.

6. The method of claim 1, further comprising analyzing said initial set of data records.

7. The method of claim 6, wherein said analyzing said initial set of data records further comprises analyzing validity of attributes of said initial set of data records.

8. The method of claim 1, wherein said analyzing said buckets further comprises analyzing statistics associated with said buckets, analyzing a bucket size distribution, analyzing said buckets by size, analyzing said buckets by composition, analyzing a bulk cross match comparison distribution, analyzing members by bucket count, analyzing member bucket values, analyzing member bucket frequencies, analyzing a member comparison distribution, or a combination thereof.

9. The method of claim 1, further comprising analyzing error rates associated with said initial set of data records, wherein said error rates comprise a record error rate and a person error rate.

10. The method of claim 1, wherein said configuration of said system comprises a clerical review threshold and an autolink threshold and wherein said clerical review threshold and said autolink threshold are indicative of tolerance of said system to false positive and false negative rates in matching said initial set of data records, further comprising analyzing said clerical review threshold and said autolink threshold.

11. A computer readable storage medium storing computer instructions executable by a processor, wherein when executed by said processor said computer instructions cause a computer to:

produce a configuration of a system utilizing an initial set of data records;

create buckets based on said initial set of data records or a subset thereof according to a bucketing strategy associated with said configuration of said system;

analyze said buckets and an effect of said buckets on performance of said system; and

enable a user to change said bucketing strategy.

12. The computer readable storage medium of claim 11, wherein when executed by said processor said computer instructions further cause said computer to display an algorithm editor through which an algorithm utilized in creating said buckets is editable by said user.

13. The computer readable storage medium of claim 11, wherein said bucketing strategy is associated with an entity type and wherein when executed by said processor said computer instructions further cause said computer to display an entity analysis tool through which entities categorized as having said entity type in said system are analyzable by said user.

14. The computer readable storage medium of claim 11, wherein when executed by said processor said computer instructions further cause said computer to provide a plurality of functions through said entity analysis tool, wherein said plurality of functions enables said user to analyze an entity size distribution, analyze said entities by size, analyze said entities by composition, analyze a score distribution associated with said entities, and analyze member comparisons associated with said entities.

15. The computer readable storage medium of claim 11, wherein when executed by said processor said computer instructions further cause said computer to display a data analysis tool through which said initial set of data records is analyzable by said user.

16. The computer readable storage medium of claim 15, wherein when executed by said processor said computer Instructions further cause said computer to provide at least one function through said data analysis tool, wherein said at least one function enables said user to analyze attribute validity of said initial set of data records.

17. The computer readable storage medium of claim 11, wherein when executed by said processor said computer instructions further cause said computer to display a bucket analysis tool through which said buckets and statistics associated with said buckets are analyzable by said user.

18. The computer readable storage medium of claim 17, wherein when executed by said processor said computer instructions further cause said computer to provide a plurality of functions through said bucket analysis tool, wherein said plurality of functions enables said user to analyze a bucket size distribution, analyze said buckets by size, analyze said buckets by composition, analyze a bulk cross match comparison distribution, analyze members by bucket count, analyze member bucket values, analyze member bucket frequencies, and analyze a member comparison distribution.

19. The computer readable storage medium of claim 11, wherein when executed by said processor said computer instructions further cause said computer to display a linkage analysis tool through which said error rates associated with said initial set of data records are analyzable by said user, wherein said error rates comprise a record error rate and a person error rate.

20. A computer system for analyzing an identity hub, comprising:

at least one processor; and

at least one computer readable storage medium accessible by said at least one processor and storing computer instructions executable by said at least one processor, wherein when executed by said at least one processor said computer instructions cause said computer system to display a graphical user interface interfacing a plurality of tools comprising a configuration editor, an algorithm editor, a data analysis tool, an entity analysis tool, a bucket analysis tool, and a linkage analysis tool, wherein said configuration editor allow a user to create or load a configuration of said identity hub locally utilizing an initial set of data records from information sources coupled to said identity hub, wherein said algorithm editor enables said user to edit an algorithm utilized in creating buckets based on said initial set of data records, wherein said data analysis tool enables said user to analyze attribute validity of said initial set of data records, wherein said entity analysis tools enables said user to analyze entities associated with said initial set of data records, wherein said bucket analysis tool enables said user to analyze said buckets and an effect of said buckets on said identity hub, and wherein said linkage analysis tool enables said user to analyze error rates associated with linking member records from said initial set of data records and thresholds utilized in scoring derivatives of said initial set of data records.