Method for visualizing information in a data warehousing environment

• US 7,320,001 B1
• Filed: 01/13/2000
• Issued: 01/15/2008
• Est. Priority Date: 01/15/1999
• Status: Expired due to Fees

• Current Assignee: Hon Hai Precision Industry Co., Ltd.
• Original Assignee: Hon Hai Precision Industry Co., Ltd.
• Inventors: Chen, Li-Wen
• Primary Examiner(s): Colbert, Ella
• Application Number:
  US09/483,385
• Time in Patent Office: 2,924 Days
• Field of Search: 707/1, 707/10, 707/100, 707/101, 707/104.1, 707/200, 707/201, 707/206, 707/102, 705/1, 705/5, 705/7, 705/14, 705/16, 705/26, 705/28, 705/30, 705/35, 705/39, 705/44, 706/52, 717/5, 717/102, 717/104, 717/105
• US Class Current: 1/1
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• 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
• CPC Class Codes: Y10S 707/99952 Coherency, e.g. same view to multiple users
• CPC Class Codes: Y10S 707/99953 Recoverability

Abstract

According to the invention, techniques for visualizing customer data contained in databases, data marts and data warehouses. In an exemplary embodiment, the invention provides a method for graphically analyzing relationships in data from one or more data sources of an enterprise. The method can be used with many popular visualization tools, such as On Line Analytical Processing (OLAP) tools and the like. The method is especially useful in conjunction with 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 display data from a variety of sources in order to provide visual representations of data in a data warehousing environment.

Claims

1. A method for analyzing information in at least one source database, said method comprising:

receiving a definition of a reverse star schema meta-model;

generating a data warehouse populated with the information from the source database and in accordance with the reverse star schema meta-model;

receiving a definition of at least one of a plurality of customer profile groups;

receiving input indicating at least one quantity of interest in the information;

receiving a definition for a data model;

dynamically creating at least one generated database based upon the data warehouse and the data model and configured to the quantity of interest, further comprising;

creating at least one first dimension table based upon the data schema and the quantity of interest; and

creating at least one fact table based upon the data schema, the quantity of interest and the information; and

displaying at least a portion of the dynamically generated database.

2. The method of claim 1, further comprising:

generating a customer profile report and wherein the information comprises business performance measures; and

wherein;

creating at least one first dimension table further comprises;

creating a customer profile hierarchy from the customer profile groups; and

creating at least one fact table further comprises;

aggregating said business performance measures according to said customer profile hierarchy.

3. The method of claim 1 further comprising generating an operation report, and wherein the information comprises business performance measures, and wherein:

creating at least one fact table further comprises;

aggregating said business performance measures; and

filtering said customer profiles.

4. The method of claim 1 further comprising generating a customer behavior report, and wherein the information comprises customer records, and wherein:

creating at least one first dimension table further comprises;

creating at least one of a plurality of customer profiling dimensions based upon the at least one of a plurality of customer profile groups received; and

creating at least one fact table further comprises;

aggregating customer records based on said at least one of a plurality of customer profiling dimensions.

5. The method of claim 1 further comprising:

creating a list of customers for each one of the plurality of customer profile groups;

creating at least one intermediary data structure to manage the list of customers; and

creating customer classification components in a meta model for each customer profile group.

6. The method of claim 1 wherein said information comprises at least one of telecommunications information, financial information, retail marketing information, insurance information, and health care information.

7. The method of claim 1, further comprising:

receiving a selection of a targeted customer segment of interest as the quantity of interest;

generating at least one of a plurality of targeted customer segment tables based upon the dynamically generated database; and

providing the targeted customer segment tables to external applications.

8. The method of claim 1, wherein the dynamically generated database further comprises:

receiving an input from an on-line application processor (OLAP);

transforming the input into a database query based upon the data model; and

providing information in response to the database query.

9. A computer readable medium comprising one or more instructions for causing a processor to perform the steps of:

receiving a definition of a reverse star schema meta-model;

generating a data warehouse populated with the information from a source database and in accordance with the reverse star schema meta-model;

receiving a definition of at least one of a plurality of customer profile groups;

receiving input indicating at least one quantity of interest in the information;

receiving a definition for a data model;

dynamically creating at least one generated database based upon the data warehouse and the data model and configured to the quantity of interest, further comprising;

creating at least one first dimension table based upon the data schema and the quantity of interest; and

creating at least one fact table based upon the data schema, the quantity of interest and the information; and

displaying at least a portion of the dynamically generated database.