System and method for providing a data warehouse in accordance with a virtual schema

• US 20020116389A1
• Filed: 11/29/2001
• Published: 08/22/2002
• Est. Priority Date: 01/15/1999
• Status: Active Grant

• Current Assignee: Byteweavr, LLC (Ascend Innovation Management, LLC)
• Original Assignee: Metaedge
• Inventors: Chen, Li-Wen, Ortiz, Juan J.
• Granted Patent: US 7,319,996 B2
• Time in Patent Office: Days
• US Class Current: 707/103R
• CPC Class Codes: G06F 16/30 of unstructured textual data document management systems G06F16/93
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

According to the invention, techniques for organizing information from systems in a data warehousing environment are provided. In an exemplary embodiment, the invention provides a method for analyzing data from one or more data sources of an enterprise. The method provides a meta-model based technique for modeling the enterprise data. The enterprise is typically a business activity, but can also be other loci of human activity. Embodiments according to the invention can translate data from a variety of sources to particular database schema in order to provide organization to a data warehousing environment.

Claims

1. A computer based method for analyzing data contained in at least one of a plurality of data sources of an enterprise, said method comprising:

providing a model for said at least one of a plurality of data sources of said enterprise;

forming a data organization for said model;

creating a database having said data organization;

translating data from said at least one of a plurality of data sources to said data organization, to form a plurality of translated data;

incorporating said translated data into said database; and

performing analysis on said translated data in said database, wherein said data organization comprises at least one of a plurality of data, said data comprising;

(a) at least one identity element; and

(b) at least one attribute element, wherein said identity element and said attribute element have at least one of a plurality of relationships between one another.

2. The method of claim 1 wherein said model further comprises:

a focal group, said focal group comprising;

at least one of a plurality of classification components; and

at least one of a plurality of core components; and

a customized group, said customized group comprising;

at least one of a plurality of customer activity components; and

at least one of a plurality of activity lookup components;

wherein said customized group has at least one of a plurality of relationships with said focal group.

3. The method of claim 2 wherein said classification components comprises customers'"'"' categorization of information related to business processes.

4. The method of claim 2 wherein said activity components comprises business transactions.

5. The method of claim 2 wherein said activity components comprises business events.

6. The method of claim 2 wherein said activity components comprises business activities.

7. The method of claim 2 wherein said activity components comprises business measures.

8. The method of claim 2 wherein said activity lookup components comprises reference information for customers'"'"' business transactions.

9. The method of claim 2 wherein said activity lookup components comprises reference information for customers'"'"' business events.

10. The method of claim 2 wherein said activity lookup components comprises reference information for customers'"'"' business activities.

11. The method of claim 2 wherein said activity lookup components comprises reference information for customers'"'"' business measures.

12. The method of claim 1 wherein said data organization further comprises at least one of a plurality of core components, said core components comprising:

a customer identifier; and

at least one of a plurality of classification components, wherein said classification components has at least one of a plurality of relationships with said core components.

13. The method of claim 12 wherein said core components further comprises an account identifier.

14. The method of claim 12 wherein said classification components comprises a sales channel.

15. The method of claim 12 wherein said classification components comprises a customer region.

16. The method of claim 12 wherein said classification components comprises a customer profile.

17. The method of claim 12 wherein said classification components comprises a demographic profile.

18. The method of claim 1 wherein said enterprise comprises a business.

19. The method of claim 1 wherein said data comprises telecommunications information.

20. The method of claim 1 wherein said data comprises financial information.

21. The method of claim 1 wherein said data comprises retail marketing information.

22. The method of claim 1 wherein said data comprises insurance information.

23. The method of claim 1 wherein said data comprises health care information.

25. The method of claim 24 further comprising defining for said attributes at least one of a plurality of foreign keys.

26. The method of claim 24 further comprising:

defining application-specific entities for said customer activity components.

27. The method of claim 26 further comprising:

defining at least one of a plurality of attributes for said application-specific entities.

28. The method of claim 24 wherein said deriving said data types is performed automatically.

29. The method of claim 28 further comprising:

providing to users the capability to make changes to said data types if they choose not to use the automatically derived ones.

24. A computer based method for performing customer analysis of contents of at least one of a plurality of data sources, said method comprising:

selecting a template from a plurality of pre-defined ones, said templates embodying a plurality of characteristics of a business;

selecting at least one of a plurality of customer entities from a plurality of pre-defined ones to form a focal group of customer entities, said selecting based upon said template;

defining at least one of a plurality of customer transaction entities and at least one of a plurality of attributes of said customer transaction entities to form a customized group of customer activity components;

defining at least one of a plurality of customer event types in said customer activity components, wherein said customer event types comprise attributes of said customer transaction entities in said customer activity components;

selecting at least one of a plurality of data tables and at least one of a plurality of attributes of said data tables to form a data schema, wherein said data schema is a reverse star data schema;

determining at least one of a plurality of attributes based on data types of tables of said data source;

determining for said attributes at least one of a plurality of primary keys;

creating a data warehouse database from said data schema;

creating at least one of a plurality of data mapping rules, said mapping rules providing translation information for tables and attributes of said data sources to said data warehouse.

30. A method for integrating customer data analysis tools with at least one of a plurality of database systems, said method comprising:

installing a data warehouse database, said database having a reverse star schema data model, said reverse star schema mapping to data in said at least one of a plurality of database systems;

performing customer data analysis using said data warehouse database.

31. The method of claim 30 wherein said customer data analysis comprises customer purchasing behavior analysis.

32. The method of claim 30 wherein said customer data analysis comprises customer market segmentation analysis.

33. The method of claim 30 wherein said customer data analysis comprises customer valuation analysis.

34. The method of claim 30 wherein said customer data analysis comprises customer chum analysis.