SQL-based analytic algorithms

• US 6,687,695 B1
• Filed: 04/02/2001
• Issued: 02/03/2004
• Est. Priority Date: 10/02/1998
• Status: Expired due to Term

• Current Assignee: Teradata US, Inc. (Teradata Corporation)
• Original Assignee: NCR Corporation
• Inventors: Anand, Tej, Miller, Timothy Edward, Brye, Todd Michael, Rollins, Anthony Lowell, Tate, Brian Don, Hildreth, James Dean, Pricer, James Edward
• Primary Examiner(s): Homere, Jean R.
• Assistant Examiner(s): PHAM, KHANH B
• Application Number:
  US09/806,742
• Time in Patent Office: 1,037 Days
• Field of Search: 707/6, 707/2, 707/3, 707/4, 707/5, 707/101, 707/102
• US Class Current: 1/1
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G06F 2216/03 Data mining
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

A method, apparatus, and article of manufacture for performing data mining applications in a relational database management system. At least one analytic algorithm (110) is performed by a computer directly against a relational database (116), wherein the analytic algorithm includes SQL statements performed by the relational database management system (114) and optional programmatic iteration, and the analytic algorithm creates at least one analytic model within an analytic logical data model from data residing in the relational database.

Claims

1. A computer-implemented system for performing data mining applations, comprising:

(a) a computer having one or more data storage devices connected thereto;

(b) a relational database management system, executed by the computer, for managing a relational database stored on the data storage devices; and

(c) at least one t algorithm performed by the computer, wherein the analytic algorithm includes SQL statements performed by the relational database management system directly against the relational database and optional programmatic iteration, the analytic algorithm creates at least one analytic model within a analytic logical data model from data residing in the relational database, and the analytic algorithm is implemented by a Data Reduction Utility Program chat reduces data from the relational database in bulk using SQL followed by a non-SQL iterative program.

2. The computer-implemented system of claim 1, wherein the analytic algorithm provides statistical and machine learning methods for creating the analytic logical data model.

3. The computer-implemented system of claim 1, wherein the analytic algorithm is implemented in Extended ANSI SQL.

4. The computer-implemented system of claim 3, wherein the analytic algorithm operates against a set of tables in the relational database, and the Extended ANSI SQL build relationships among data elements in the tables.

5. The computer-implemented system of claim 4, wherein the Extended ANSI SQL analyzes the relationships to determine how the relationships change.

6. The computer-implemented system of claim 1, wherein the analytic algorithm is implemented in a Call Level Interface (CLI) that processes data from the relational database using SQL and programmatic iteration.

7. The computer-implemented system of claim 6, wherein the CLI is used with SQL to perform computations, aggregations, and/or ordering on the data from the relational database.

8. The computer-implemented system of claim 1, wherein the Data Reduction Utility Program provides a sequence of Extended ANSI SQL followed by programmatic iteration.

9. A method for performing data mining applications, comprising:

(a) managing a relational database stored on one or more data storage devices connected to a computer; and

(b) performing at least one analytic algorithm in the computer, wherein the analytic algorithm includes SQL statements performed by a relational database management system directly against the relational database and optional programmatic iteration, the analytic algorithm creates at leaser one analytic model within an analytic logical data model from data residing in the relational database, and the an c algorithm is implemented by a Data Reduction Utility Program that reduces data from the relational database in bulk using SQL followed by a non-SQL iterative program.

10. The method of claim 9, wherein the analytic algorithm provides statistical and machine learning methods for creating the analytic logical data model.

11. The method of claim 9, wherein the analytic algorithm is implemented in Extended ANSI SQL.

12. The method of claim 11, wherein the analytic algorithm operates against a set of tables in the relational database, and the Extended ANSI SQL build relationships among data elements in the tables.

13. The method of claim 12, wherein the Extended ANSI SQL analyzes the relationships to determine how the relationships change.

14. The method of claim 9, wherein the analytic algorithm is implemented in a Call Level Interface (CLI) that processes data from the relational database using SQL and programmatic iteration.

15. The method of claim 14, wherein the CLI is used with SQL to perform computations, aggregations, and/or ordering on the data from the relational database.

16. The method of claim 9, wherein the Data Reduction Utility Program provides a sequence of Extended ANSI SQL followed by programmatic iteration.

17. An article of manufacture comprising logic embodying a method for performing data mining applications, comprising:

(a) managing a relational database stored on one or more data storage devices connected to a computer; and

(b) performing at least one analytic algorithm in the completer, wherein the analytic algorithm includes SQL statements performed by a relational database management system directly against the relational database and optional programmatic iteration, the analytic algorithm creates at least one analytic model within an analytic logical data model from data residing in the relational database, and the analytic algorithm is implemented by a Data Reduction Utility Program that reduces data from the relational database in bulk using SQL followed by a non-SQL iterative program.

18. The article of claim 17, wherein the analytic algorithm provides statirical and machine learning methods for creating the analytic logical data model.

19. The article of claim 17, wherein the analytic algorithm is implemented in Extended ANSI SQL.

20. The article of claim 19, wherein the analytic algorithm operates against a set of tables in the relational database, and the Extended ANSI SQL build relationships among data elements in the tables.

21. The article of claim 20, wherein the Extended ANSI SQL analyzes the relationships to determine how the relationships change.

22. The article of claim 17, wherein the analytic algorithm is implemented in a Call Level Interface (CLI) that processes data from the relational database using SQL and programmatic iteration.

23. The article of claim 22, wherein the CLI is used with SQL to perform computations, aggregations, and/or ordering on the data from the relational database.

24. The article of claim 17, a wherein the Data Reduction Utility Prom provides a sequence of Extended ANSI SQL followed by programmatic iteration.