Data Integration Method and System

• US 20110055173A1
• Filed: 09/28/2010
• Published: 03/03/2011
• Est. Priority Date: 02/18/2003
• Status: Active Grant

• Current Assignee: Dun & Bradstreet Corp., DUN & Bradstreet Incorporated (Dun & Bradstreet Corp.), Hoover's Incorporated (Dun & Bradstreet Holdings, Inc.)
• Original Assignee: Dun & Bradstreet Corp.
• Inventors: Duckworth, Alan, Sharif, Ahmad Tariq, Lucas, Christopher John, Prevoznak, Michael E., Seckler, Maria P., Stoker, Sandra L., Benke, Charles R.
• Granted Patent: US 8,346,790 B2
• Time in Patent Office: Days
• US Class Current: 707/692
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

A computer implemented method for ensuring the quality of processed corporate entity data, the method comprising: sequentially processing the corporate entity data through a series of serially connected drivers, the serially connected drivers comprise a data collection driver, an entity matching driver, an identification number driver, a corporate linkage driver, and a predictive indicator driver; and conducting a quality assurance of the corporate entity data as it is processed in each of the driver, wherein the quality assurance comprises: (i) sampling the corporate entity data from each the driver periodically, thereby generating sample data; (ii) evaluating the sample data; and (iii) adjusting the processing based upon the evaluation, thereby producing high quality data.

Claims

1. A computer implemented method for ensuring quality of processed corporate entity data, said method comprising:

sequentially processing said corporate entity data through a series of serially connected drivers, said serially connected drivers comprise a data collection driver, an entity matching driver, an identification number driver, a corporate linkage driver, and a predictive indicator driver; and

conducting a quality assurance of said corporate entity data as it is processed in each of said driver, wherein said quality assurance comprises;

sampling said corporate entity data from each said driver periodically, thereby generating sample data;

evaluating said sample data; and

adjusting said processing based upon said evaluating, thereby producing high quality data.

2. The method according to claim 1, wherein said evaluating of said sample data consists of at least one step selected from the group consisting of:

auditing, validating, normalizing, correcting, and updating of said corporate entity data.

3. The method according to claim 1, wherein said corporate entity data is initially processed through said data collection driver to produce primary corporate entity data, said primary corporate entity data is then processed by said entity matching driver, said primary corporate entity data is processed by said entity matching driver where if not matched to previously stored data, then the unmatched primary corporate entity data is sent to said identification number driver where an identification number is assigned thereto, and if matched to said previously stored data, then the matched primary corporate entity data from said entity matching driver and/or primary corporate entity data having an assigned identification number applied in said identification number driver are processed by said corporate linkage driver, and thereafter said primary corporate entity data from said corporate linkage driver is processed by said predictive indicator driver.

4. The method according to claim 1, wherein said data collection driver mergers said corporate entity data from a variety of sources.

5. The method according to claim 1, wherein said entity matching driver matches said corporate entity data with a stored identification number.

6. The method according to claim 5, wherein said identification number driver assigns an identification number to said corporate entity data that was number matched in by said entity matching driver.

7. The method according to claim 6, wherein said corporate linkage driver builds corporate families based upon said corporate entity data which has been matched or assigned said identification number.

8. The method according to claim 1, wherein said predictive indicator driver uses statistical analysis to rate an entity'"'"'s past performance to indicate the likelihood that said entity will perform the same way in the future.

9. A computer system for ensuring the quality of processed corporate entity data, said system comprising:

a data collection driver;

an entity matching driver;

an identification number driver;

a corporate linkage driver

a predictive indicator driver; and

a processor which sequentially filters said corporate entity data through the serially connected data collection driver, entity matching driver, identification number driver, corporate linkage driver, and predictive indicator driver, and

wherein said processor conducts a quality assurance of said corporate entity data as it is processed in each of said driver, wherein said quality assurance comprises;

sampling said corporate entity data from each said driver periodically, thereby generating sample data;

evaluating said sample data; and

adjusting said processing based upon said evaluation, thereby producing high quality data.

10. The system according to claim 9, wherein said evaluating of said sample data consists of at least one step selected from the group consisting of:

auditing, validating, normalizing, correcting, and updating of said corporate entity data.

11. The system according to claim 9, wherein said processor:

processes said corporate entity data through said data collection driver to produce primary corporate entity data,

processes said primary corporate entity data by said entity matching driver to determine if an identification number has been previously assigned to said primary corporate entity data,

if said corporate entity data was not previously assigned said identification number, then the unmatched primary corporate entity data is sent to said identification number driver where an identification number is assigned thereto, and

if said corporate entity data was previously assigned said identification number, then the matched primary corporate entity data from said entity matching driver and/or primary corporate entity data having an assigned identification number applied in said identification number driver are processed by said corporate linkage driver, and

processes said primary corporate entity data from said corporate linkage driver by said predictive indicator driver.

12. The system according to claim 9, wherein said data collection mergers said corporate entity data from a variety of sources.

13. The system according to claim 9, wherein said entity matching driver matches said corporate entity data with a stored identification number.

14. The system according to claim 13, wherein said identification number driver assigns an identification number to said corporate entity data that was number matched in by said entity matching driver.

15. The system according to claim 14, wherein said corporate linkage driver builds corporate families based upon said corporate entity data which has been matched or assigned said identification number.

16. The system according to claim 9, wherein said predictive indicator driver uses statistical analysis to rate an entity'"'"'s past performance to indicate the likelihood that said entity will perform the same way in the future.

17. A machine-readable medium storing executable instructions for data integration, the instructions comprising:

sequentially processing said corporate entity data through a series of serially connected drivers, said serially connected drivers comprise a data collection driver, an entity matching driver, an identification number driver, a corporate linkage driver, and a predictive indicator driver; and

conducting a quality assurance of said corporate entity data as it is processed in each of said driver, wherein said quality assurance comprises;

sampling said corporate entity data from each said driver periodically, thereby generating sample data;

evaluating said sample data; and

adjusting said processing based upon said evaluation, thereby producing high quality data.

18. The machine-readable medium according to claim 17, wherein said evaluating of said sample data consists of at least one step selected from the group consisting of:

auditing, validating, normalizing, correcting, and updating of said corporate entity data.

19. The machine-readable medium according to claim 17, wherein said corporate entity data is initially processed through said data collection driver to produce primary corporate entity data, said primary corporate entity data is then processed by said entity matching driver, said primary corporate entity data is processed by said entity matching driver where if not matched to previously stored data, then the unmatched primary corporate entity data is sent to said identification number driver where an identification number is assigned thereto, and if matched to said previously stored data, then the matched primary corporate entity data from said entity matching driver and/or primary corporate entity data having an assigned identification number applied in said identification number driver are processed by said corporate linkage driver, and thereafter said primary corporate entity data from said corporate linkage driver is processed by said predictive indicator driver,