Analysis of a system for matching data records

• US 8,799,282 B2
• Filed: 09/26/2008
• Issued: 08/05/2014
• Est. Priority Date: 09/28/2007
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Goldenberg, Glenn, Schumacher, Scott, Woods, Jason
• Primary Examiner(s): Badawi, Sherief
• Assistant Examiner(s): Mitiku, Berhanu
• Application Number:
  US12/239,448
• Publication Number:
  US 20090089630A1
• Time in Patent Office: 2,139 Days
• Field of Search: 707/695, 707/999.013, 707/999.004, 707/999.001, 707/688, 707/693, 707/737, 707/957, 707/999.002, 707/999.006, 707/999.007, 711/112, 711170-172, 711219-220, 709217-219
• US Class Current: 707/736
• 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 computer-implemented method for analyzing a system for matching data records, the method comprising:

producing a configuration of said system, the configuration of the system applying a bucketing strategy operable to create buckets by comparing sets of one or more attributes of initial data records with corresponding attributes of candidate data records in said system, wherein each bucket is associated with a corresponding set of attributes;

analyzing buckets created according to the bucketing strategy associated with said configuration of said system, wherein said buckets each comprise candidate data records with the corresponding set of attributes similar to those of the initial data records and are used to associate data records with a common entity, and 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;

analyzing an effect of said buckets on performance of said system to determine and link data records associated with a common entity; and

changing said bucketing strategy accordingly to alter determination of the association of data records with the common entity.

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 validity of attributes of said initial set of data records.

7. 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.

8. 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.

9. A non-transitory 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;

create buckets according to a bucketing strategy associated with said configuration of said system by comparing sets of one or more attributes of initial data records with corresponding attributes of candidate data records in said system, wherein each bucket is associated with a corresponding set of attributes, and wherein said buckets each comprise candidate data records with the corresponding set of attributes similar to those of the initial data records and are used to associate data records with a common entity;

analyze said buckets and an effect of said buckets on performance of said system to determine and link data records associated with a common entity, wherein said analyzing said buckets further comprises analyzing statistics associated with said buckets, analyzing a bucket size distribution, anal ing 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; and

change said bucketing strategy to alter determination of the association of data records with the common entity.

10. The non-transitory computer readable storage medium of claim 9, 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 edited.

11. The non-transitory computer readable storage medium of claim 9, 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 analyzed.

12. The non-transitory computer readable storage medium of claim 9, wherein when executed by said processor said computer instructions further cause said computer to provide a plurality of functions through an entity analysis tool, wherein said plurality of functions enables analysis of an entity size distribution, said entities by size, said entities by composition, a score distribution associated with said entities, and member comparisons associated with said entities.

13. The non-transitory computer readable storage medium of claim 9, 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 analyzed.

14. The non-transitory computer readable storage medium of claim 13, 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 analysis of attribute validity of said initial set of data records.

15. The non-transitory computer readable storage medium of claim 9, 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 analyzed.

16. The non-transitory computer readable storage medium of claim 9, wherein when executed by said processor said computer instructions further cause said computer to display a linkage analysis tool through which error rates associated with said initial set of data records are analyzed, wherein said error rates comprise a record error rate and a person error rate.

17. 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 creates or loads 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 edits an algorithm utilized in creating buckets based on said initial set of data records to alter determination of an association of data records with a common entity, wherein said buckets are created by comparing sets of one or more attributes of the initial data records with corresponding attributes of candidate data records and each bucket is associated with a corresponding set of attributes, and wherein said buckets each comprise candidate data records with the corresponding set of attributes similar to those of the initial data records and are used to associate data records with the common entity;

wherein said data analysis tool enables analysis of attribute validity of said initial set of data records;

wherein said entity analysis tool enables analysis of entities associated with said initial set of data records;

wherein said bucket analysis tool enables analysis of said buckets and an effect of said buckets on said identity hub for determining and linking data records associated with the common entity; and

wherein said linkage analysis tool enables analysis of 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.