Incorporating predicrive models within interactive business analysis processes

• US 7,249,048 B1
• Filed: 06/30/2000
• Issued: 07/24/2007
• Est. Priority Date: 06/30/2000
• Status: Active Grant

• Current Assignee: Teradata US, Inc. (Teradata Corporation)
• Original Assignee: NCR Corporation
• Inventors: O'Flaherty, Kenneth W.
• Primary Examiner(s): MEINECKE DIAZ, SUSANNA M
• Application Number:
  US09/608,595
• Time in Patent Office: 2,580 Days
• Field of Search: 707/6, 709/224, 705/7, 705/8, 705/10
• US Class Current: 705/7.27
• CPC Class Codes: G06F 16/2428 Query predicate definition using graphical user interfaces, including menus and forms G06F16/2423 takes precedence
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G06Q 10/0633 Workflow analysis
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0204 Market segmentation

Abstract

A Customer Relationship Management (CRM) system that incorporates predictive models. The system is used by business users who are unfamiliar with the art of data mining. The predictive model, which is constructed by a model-building mechanism in a data mining subsystem, accepts the appropriate input attributes, performs calculations against a segment comprised of records, and generates an output attribute.

Claims

1. A method for using predictive models within a computer-implemented business analysis environment, comprising:

(a) applying a derived measure against a segment, wherein the derived measure comprises a predictive model previously-built by a model-building mechanism in a data mining system, wherein the derived measure is invoked within an application template that is a sequence of one or more icons representing segments, filters, measures and functions and the icons are linked together in a workflow, and wherein the application template is used to save the sequence of icons linked together in the workflow; and

(b) generating output for the segment from the predictive model in the form of measure values.

2. The method of claim 1, wherein connecting arrows between the icons determine a sequence of execution and a flow of data.

3. The method of claim 2, wherein the application template is constructed in a visual programming environment by dragging and dropping the icons in a graphical user interface and then linking together the icons to create the sequence of steps that comprise the workflow of the application template.

4. The method of claim 1, wherein the application templates are reused or modified by users.

5. The method of claim 1, wherein a segment is a grouping of data elements from a database organized about one or more attributes.

6. The method of claim 1, wherein a filter defines one or more attribute constraints applied to a segment.

7. The method of claim 1, wherein a profile is a labeled collection of attributes of a segment.

8. The method of claim 1, wherein a measure is an expression applied to a segment.

9. The method of claim 1, wherein the computer-implemented business analysis environment includes an object model, and the segments, attributes, filters, and measures comprise objects.

10. The method of claim 9, wherein operations upon the objects are translated into SQL statements that access corresponding tables and columns in a relational database.

11. The method of claim 1, wherein the predictive model comprises one or more SQL statements that access tables and columns in a relational database.

12. The method of claim 1, wherein the predictive model comprises one or more statements executed by a database management system.

13. The method of claim 12, wherein the statements access data stored in the database management system.

14. The method of claim 1, wherein the model-building mechanism comprises an analytic algorithm for rule induction performed against data stored in a database management system to create the predictive model.

15. A computer-implemented system for using predictive models within a computer-implemented business analysis environment, comprising:

(a) means for applying a derived measure against a segment, wherein the derived measure comprises a predictive model previously-built by a model-building mechanism in a data mining system, wherein the derived measure is invoked within an application template that is a sequence of one or more icons representing segments, filters, measures and functions and the icons are linked together in a workflow, and wherein the application template is used to save the sequence of icons linked together in the workflow; and

(b) means for generating output for the segment from the predictive model in the form of measure values.

16. The system of claim 15, wherein connecting arrows between the icons determine a sequence of execution and a flow of data.

17. The system of claim 16, wherein the application template is constructed in a visual programming environment by dragging and dropping the icons in a graphical user interface and then linking together the icons to create the sequence of steps that comprise the workflow of the application template.

18. The system of claim 15, wherein the application templates are reused or modified by users.

19. The system of claim 15, wherein a segment is a grouping of data elements from a database organized about one or more attributes.

20. The system of claim 15, wherein a filter defines one or more attribute constraints applied to a segment.

21. The system of claim 15, wherein a profile is a labeled collection of attributes of a segment.

22. The system of claim 15, wherein a measure is an expression applied to a segment.

23. The system of claim 15, wherein the computer-implemented business analysis environment includes an object model, and the segments, attributes, filters, and measures comprise objects.

24. The method of claim 23, wherein operations upon the objects are translated into SQL statements that access corresponding tables and columns in a relational database.

25. The system of claim 15, wherein the predictive model comprises one or more SQL statements that access tables and columns in a relational database.

26. The system of claim 15, wherein the predictive model comprises one or more statements executed by a database management system.

27. The system of claim 26, wherein the statements access data stored in the database management system.

28. The system of claim 27, wherein the model-building mechanism comprises an analytic algorithm for rule induction performed against data stored in a database management system to create the predictive model.

29. An article of manufacture embodying computer-executable code that, when executed by a computer, performs a method for using predictive models within a computer-implemented business analysis environment, the method comprising:

(a) applying a derived measure against a segment, wherein the derived measure comprises a predictive model previously-built by a model-building mechanism in a data mining system, wherein the derived measure is invoked within an application template that is a sequence of one or more icons representing segments, filters, measures and functions and the icons are linked together in a workflow, and wherein the application template is used to save the sequence of icons linked together in the workflow; and

(b) generating output for the segment from the predictive model in the form of measure values.

30. The article of manufacture of claim 29, wherein connecting arrows between the icons determine a sequence of execution and a flow of data.

31. The article of manufacture of claim 30, wherein the application template is constructed in a visual programming environment by dragging and dropping the icons in a graphical user interface and then linking together the icons to create the sequence of steps that comprise the workflow of the application template.

32. The article of manufacture of claim 29, wherein the application templates are reused or modified by users.

33. The article of manufacture of claim 29, wherein a segment is a grouping of data elements from a database organized about one or more attributes.

34. The article of manufacture of claim 29, wherein a filter defines one or more attribute constraints applied to a segment.

35. The article of manufacture of claim 29, wherein a profile is a labeled collection of attributes of a segment.

36. The article of manufacture of claim 29, wherein a measure is an expression applied to a segment.

37. The article of manufacture of claim 29, wherein the computer-implemented business analysis environment includes an object model, and the segments, attributes, filters, and measures comprise objects.

38. The method of claim 37, wherein operations upon the objects are translated into SQL statements that access corresponding tables and columns in a relational database.

39. The article of manufacture of claim 29, wherein the predictive model comprises one or more SQL statements that access tables and columns in a relational database.

40. The article of manufacture of claim 29, wherein the predictive model comprises one or more statements executed by a database management system.

41. The article of manufacture of claim 40, wherein the statements access data stored in the database management system.

42. The article of manufacture of claim 29, wherein the model-building mechanism comprises an analytic algorithm for rule induction performed against data stored in a database management system to create the predictive model.