Forecasting system and method using change data based database storage for efficient ASP and web application

• US 9,026,487 B2
• Filed: 11/03/2008
• Issued: 05/05/2015
• Est. Priority Date: 04/26/2004
• Status: Active Grant

• Current Assignee: Ignite Enterprise Software Solutions, Inc. (Infonow Corporation)
• Original Assignee: Right90, Inc. (ESW Capital, LLC)
• Inventors: Orumchian, Kim, Stabenow, Art, Skelton, Dean, Petiot, David
• Primary Examiner(s): Vy, Hung T
• Application Number:
  US12/264,123
• Publication Number:
  US 20090150368A1
• Time in Patent Office: 2,374 Days
• Field of Search: 707/600, 705/26
• US Class Current: 707/600
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06F 2216/03 Data mining
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• 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 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99956 File allocation

Abstract

In one embodiment, a system is provided. The system includes a first client. The system also includes an analysis server coupled to the first client. The system further includes a first customer database of information coupled to the analysis server. The first customer database is to embody forecast data and to receive essentially real-time updates to the forecast data. The first customer database supports an OLAP cube associated with the analysis server.

Claims

1. A system comprising:

one or more computer systems that include one or more processors coupled to one or more memories that include code executable by the one or more processors to configure the one or more computer systems into one or more machines comprising;

an identification server to receive access requests from multiple client computer systems and provide a segregated system that directs users of 1 through N customers to respective 1 through N customer databases, wherein N is an integer greater than 1;

an analysis server comprising a processor and memory, coupled to the processor, wherein the memory includes code that is executable by the processor to configure the analysis server into a machine to;

receive forecast data and updates of the forecast data from multiple client computers;

segregate the data and updates of the data among the N customer databases so that each database contains data and updates of the data associated with one customer;

include an analytics and aggregation unit that includes an online analytical processing (OLAP) cube to automatically process real-time the data and updates of the data for each of the N databases to analyze and update information in partitions of the multiple customer databases, wherein the information analyzed and updated in the first partition of the multiple customer databases includes forecast data and received updates to the forecast data, and the forecast data includes at least one estimated future value; and

receive forecast data analysis requests from multiple customers; and

for each data analysis request for each customer, access the segregated customer database associated with the customer and provide the requested forecast data analysis request to the customer.

2. The system of claim 1, further comprising the at least an external first client coupled to the analysis server.

3. The system of claim 1, wherein the database comprises a customer database storing forecast data for a first customer.

4. The system of claim 3, wherein the database comprises a customer database storing forecast data for a second customer.

5. The system of claim 1, wherein the database is a database shared by a plurality of customers, including for a first customer and a second customer.

6. The system of claim 1, wherein the change partition is aggregated by the analysis server.

7. The system of claim 1, wherein the database includes a first partition and a second partition, the first partition including change data and the second partition including general data.

8. The system of claim 1, wherein updating the database includes both adding or changing data and calculating the effects of that added or changed data.

9. The system of claim 1, wherein the first partition containing change data may be calculated frequently without using too many analysis server resources due to the small amount of change data included in that second partition.

10. The system of claim 1, wherein analysis server and the database are configured to use the change data in the first partition so that the system only operates on the changed data and performs particularly well in response to a query.

11. The system of claim 10, wherein the query is communicated to both the first and second partitions and accessing data from both partitions, and having the data aggregated to appear as a single query response.

12. The system of claim 1, wherein the first partition includes only changed data, the amount of data in the first partition is smaller than the amount of data in the second partition, so that access to the data is accomplished more quickly than if responding to the query required a higher consumption of resources of the analytics and aggregation unit in analyzing and updating the information in the second partition.

13. The system of claim 1, wherein the system includes provides a world wide web interface and a world wide web hosted forecasting application.

14. The system of claim 1, wherein the system provides for concurrent access by multiple organizations.

15. The system of claim 14, wherein for the multiple organizations, the data in the database is segregated for each different one of the multiple organizations to satisfy confidentiality concerns.

16. The system of claim 15, wherein the first database includes multiple data repositories that may be separate, either logically or physically, or both logically and physically.

17. The system of claim 14, wherein:

a first user may use a first client to access the system, and access a first data repository using the analysis server including the analytics and aggregation unit; and

a second user may use a second client to access the system, and access a second data repository.

18. The system of claim 14, wherein the first user and the second user use the same the analytics and aggregation unit.

19. The system of claim 14, wherein the first user and the second user use a different the analytics and aggregation unit.

20. The system of claim 14, wherein the first user and the second user use a different instantiation of the same analytics and aggregation unit.

21. The system of claim 1, wherein processing facilities of the analytics and aggregation unit are separated, logically, or physically, or both logically and physically.

22. A method comprising:

executing code executable by one or more processors or one or more computer systems to configure the one or more computer systems into one or more machines to perform;

communicating data between an analysis server and at least an external first client and to the first customer database;

segregating data and updates of the data among N customer databases so that each database contains data and updates of the data associated with one customer, wherein N is an integer greater than 1;

receiving access requests from multiple client computer systems and provide a segregated system that directs users of 1 through N customers to the respective 1 through N customer databases;

receiving with the analysis server a query request from the external first client;

analyzing and updating information in multiple customer databases including a first of the N customer databases with an analytics and aggregation unit that includes an online analytical processing (OLAP) cube to automatically process real-time the data and updates of the data for each of the N databases, wherein the information analyzed in the first customer database includes forecast data and received updates to the forecast data, and the forecast data includes at least one estimated future value; and

operating the analytics and aggregation unit to aggregate only changed information into a change partition of the first customer database and to analyze and update the information on the basis of the changed data in the change partition;

receiving forecast data analysis requests from multiple customers; and

for each data analysis request for each customer, accessing the segregated customer database associated with the customer and provide the requested forecast data analysis request to the customer.

23. The method of claim 22, wherein the change partition containing change data may be calculated frequently without using too many analysis server resources due to the small amount of change data included in that change partition.

24. The method of claim 22, wherein analysis server and the database are configured to use the change data in the change partition so that the system only operates on the changed data and performs particularly well in response to a query.

25. The method of claim 24, wherein the query may be communicated to both the change partition and to a second main partition and accessing data from both partitions, and having the data aggregated to appear as a single query response.

26. The method of claim 25, wherein the change partition includes only changed data, the amount of data in the change partition is smaller than the amount of data in the second partition, so that access to the data is accomplished more quickly than if responding to the query required a higher consumption of resources of the analytics and aggregation unit in analyzing and updating the information in the second main partition.

27. The method of claim 22, wherein the system provides a world wide web interface and a world wide web hosted forecasting application.

28. The method of claim 22, wherein the system provides for concurrent access by multiple organizations.

29. The method of claim 28, wherein for the multiple organizations, the data in the database is segregated for each different one of the multiple organizations to satisfy confidentiality concerns.

30. The method of claim 28, wherein:

a first user may use a first client to access the system, and access a first data repository using the analysis server including the analytics and aggregation unit; and

a second user may use a second client to access the system, and access a second data repository.

31. The method of claim 30, wherein the first user and the second user use the same analytics and aggregation unit.

32. The method of claim 30, wherein the first user and the second user use a different the analytics and aggregation unit or a different instantiation of the same analytics and aggregation unit.