Data Enrichment Using Business Compendium

• US 20140067803A1
• Filed: 09/06/2012
• Published: 03/06/2014
• Est. Priority Date: 09/06/2012
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: SAP AG (SAP SE)
• Inventors: Kapadia, Vishal, Jensen, John, McBride, Geralyn
• Granted Patent: US 9,582,555 B2
• Time in Patent Office: Days
• US Class Current: 707/736
• CPC Class Codes: G06F 16/113 Details of archiving lifecycle management in storage systems G06F3/0649; backup systems G06F11/1446
• CPC Class Codes: G06F 16/20 of structured data, e.g. relational data
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/30 of unstructured textual data document management systems G06F16/93
• CPC Class Codes: G06F 16/90344 by using string matching techniques
• CPC Class Codes: G06F 16/93 Document management systems

Abstract

Embodiments relate to enrichment of a data warehouse utilizing a business compendium. Embodiments may employ a process comprising data standardization and cleansing, de-duplication of entries, and matching and enrichment, followed by manual review of an enriched record by a user. During standardization, data may be transformed into consistent content, placing correct data elements into appropriate fields, removing invalid characters, and/or standardizing names and addresses. Duplicate records are then detected and marked. During matching and enrichment, the existence of an entity (such as a supplier), may be verified by progressive matching against the business compendium. Enrichment may provide additional information regarding the entity (e.g. related to risk, diversity, and bankruptcy). The enriched record is available for manual review, allowing the user to change duplicates, matches, and parent/child linkages. Feedback from the user review may enhance accuracy of subsequent enrichment by self-learning aspects, reducing over time a need for manual review.

Claims

1. A computer-implemented method comprising:

causing an enrichment engine to receive an input data set;

causing the enrichment engine to perform standardization and cleansing of the input data set;

causing the enrichment engine to identify duplicate entries in the input data set;

causing a matching component of the enrichment engine to perform matching of non-duplicate entries of the input data set to a business compendium having data compiled from a third party source;

causing the enrichment engine to create an enriched data set including additional information based upon the matching; and

providing the enriched data set to a user for manual review.

2. A method as in claim 1 further comprising providing feedback to the matching component based upon the manual review.

3. A method as in claim 1 wherein the input data set includes a business entity, and the additional information includes ownership of the business entity.

4. A method as in claim 1 wherein the additional information comprises diversity information, government sanction information, bankruptcy information, or risk information.

5. A method as in claim 1 wherein the matching is based upon multiple priorities.

6. A method as in claim 1 wherein the matching is performed progressively according to loosening criteria.

7. A method as in claim 1 wherein the business compendium is created from a plurality of content providers.

8. A non-transitory computer readable storage medium embodying a computer program for performing a method, said method comprising:

causing an enrichment engine to receive an input data set;

causing the enrichment engine to perform standardization and cleansing of the input data set;

causing the enrichment engine to identify duplicate entries in the input data set;

causing a matching component of the enrichment engine to perform matching of non-duplicate entries of the input data set to a business compendium having data compiled from a third party source;

causing the enrichment engine to create an enriched data set including additional information based upon the matching; and

providing the enriched data set to a user for manual review.

9. A non-transitory computer readable storage medium as in claim 8 wherein the method further comprises providing feedback to the matching component based upon the manual review.

10. A non-transitory computer readable storage medium as in claim 8 wherein the input data set includes a business entity, and the additional information includes ownership of the business entity.

11. A non-transitory computer readable storage medium as in claim 8 wherein the additional information comprises diversity information, government sanction information, bankruptcy information, or risk information.

12. A non-transitory computer readable storage medium as in claim 8 wherein the matching is based upon multiple priorities.

13. A non-transitory computer readable storage medium as in claim 8 wherein the matching is performed progressively according to loosening criteria.

14. A non-transitory computer readable storage medium as in claim 8 wherein the business compendium is created from a plurality of content providers.

15. A computer system comprising:

one or more processors;

a software program, executable on said computer system, the software program configured to;

cause an enrichment engine to receive an input data set;

cause the enrichment engine to perform standardization and cleansing of the input data set;

cause the enrichment engine to identify duplicate entries in the input data set;

cause a matching component of the enrichment engine to perform matching of non-duplicate entries of the input data set to a business compendium having data compiled from a third party source;

cause the enrichment engine to create an enriched data set including additional information based upon the matching; and

providing the enriched data set to a user for manual review.

16. A computer system as in claim 15 wherein the computer program is further configured to provide feedback to the matching component based upon the manual review.

17. A computer system as in claim 15 wherein the input data set includes a business entity, and the additional information includes ownership of the business entity.

18. A computer system as in claim 15 wherein the additional information comprises diversity information, government sanction information, bankruptcy information, or risk information.

19. A computer system as in claim 15 wherein the matching is based upon multiple priorities.

20. A computer system as in claim 15 wherein the matching is performed progressively according to loosening criteria.