Methods and Systems for Calculating and Retrieving Analytic Data

• US 20140250054A1
• Filed: 03/04/2013
• Published: 09/04/2014
• Est. Priority Date: 03/04/2013
• Status: Active Grant

• Current Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Original Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Inventors: Jones, William C.
• Granted Patent: US 9,471,628 B2
• Time in Patent Office: Days
• US Class Current: 707/602
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/282 Hierarchical databases, e.g. IMS, LDAP data stores or Lotus Notes
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 10/1093 Calendar-based scheduling for persons or groups
• CPC Class Codes: G06Q 20/22 Payment schemes or models

Abstract

A data management system for calculating and retrieving analytic data involves a computing device coupled to a database. The system includes a measure data structure within the database including a measure-data element, a collection data structure within the database including a collection-data element, and a fact data structure within the database, and configured to store a fact-data element which includes an aggregated value, a link to the measure-data element, and a link to the collection-data element. The system also includes a fact-analyzer module configured to generate the aggregated value from the transaction data utilizing at least the measure-data element and the collection-data element, wherein the measure-data element defines how the aggregated value is calculated and the collection-data element defines a categorization of the aggregated value. The fact-analyzer module is also configured to store the aggregated value and links to the measure-data element and the collection-data element in the fact-data element.

Claims

1. A data management system for calculating and retrieving analytic data includes a computing device coupled to a database including transaction data, the data management system comprising:

a measure data structure within the database comprising a measure-data element;

a collection data structure within the database comprising a collection-data element;

a fact data structure within the database configured to store a fact-data element, wherein the fact-data element includes an aggregated value, a link to the measure-data element, and a link to the collection-data element; and

a fact-analyzer module configured to;

generate the aggregated value from the transaction data utilizing at least the measure-data element and the collection-data element, wherein the measure-data element defines how the aggregated value is calculated and the collection-data element defines a categorization of the aggregated value; and

store the aggregated value and links to the measure-data element and the collection-data element in the fact-data element.

2. The system in accordance with claim 1, wherein the fact-analyzer module further configured to:

recalculate the aggregated value after the aggregated value becomes stale, wherein a stale aggregated value is determined based on at least one of an elapsed amount of time, a fixed point in time, and a user input; and

store the recalculated aggregated value in the fact-data element.

3. The system in accordance with claim 1, wherein the fact-analyzer module is further configured to store at least one of an additional fact-data element, an additional measure-data element, and an additional collection-data element to the database.

4. The system in accordance with claim 1, wherein generating an aggregated value further utilizes another collection-data element from the collection data structure to define an additional categorization of the aggregated value.

5. The system in accordance with claim 1, wherein the collection data structure includes a collection type, a collection identifier, a collection name, a collection attribute, and a collection entity.

6. The system in accordance with claim 1, wherein the measure data structure includes a measure name, a measure identifier, a metric type, and a metric element.

7. The system in accordance with claim 1, further comprising:

a calendar data structure within the database comprising a calendar-data element,

wherein the fact-data element further includes a link to the calendar-data element,

wherein the fact-analyzer module is further configured to generate the aggregated value using the calendar-data element, wherein the calendar-data element defines the time range over which the aggregated value is calculated.

8. The system in accordance with claim 7, wherein the calendar data structure includes a calendar identifier, a calendar item identifier, a calendar item name, a start date, and an end date.

9. The system in accordance with claim 1, wherein the fact-analyzer module is further configured to:

receive a request for the aggregated value after storing the fact-data element;

identify the aggregated value from the fact data structure based at least in part on the request; and

output the aggregated value.

10. The system in accordance with claim 9, wherein receiving a request for the aggregated value includes identifying the fact-data element using at least the measure-data element and the collection-data element.

11. The system in accordance with claim 10, wherein receiving a request for the aggregated value includes a database cross-table operation including a join operation and a decode operation, such that each of the fact data structure, measure data structure, and collection data structure are referenced during the request.

12. A method of calculating and retrieving analytic data stored within a computing device in communication with a database, the method comprising the steps of:

storing a measure-data element in a measure data structure within the database;

storing a collection-data element in a collection data structure within the database;

calculating an aggregated value from the database based at least in part on the measure-data element and the collection-data element, wherein the measure-data element defines how the aggregated value is calculated and the collection-data element defines a categorization of the aggregated value; and

storing the aggregated value and links to the measure-data element and the collection-data element in a fact-data element of a fact data structure.

13. The method in accordance with claim 12, the method further comprising the steps of:

recalculating the aggregated value after the aggregated value becomes stale, wherein a stale aggregated value is determined based on at least one of an elapsed amount of time, a fixed point in time, and a user input; and

storing the recalculated aggregated value in the fact-data element.

14. The method in accordance with claim 12, the method further comprising the step of storing at least one of an additional fact-data element, an additional measure-data element, and an additional collection-data element to the database.

15. The method in accordance with claim 12, wherein calculating an aggregated value further includes utilizing another collection-data element from the collection data structure to define an additional categorization of the aggregated value.

16. The method in accordance with claim 12, wherein storing a collection-data element includes storing a collection type, a collection identifier, a collection name, a collection attribute, and a collection entity.

17. The method in accordance with claim 12, wherein storing a measure-data element includes storing a measure name, a measure identifier, a metric type, and a metric element.

18. The method in accordance with claim 12, the method further comprising:

storing a calendar-data element in a calendar data structure within the database,

wherein calculating an aggregated value is based at least in part on the calendar-data element, wherein the calendar-data element defines a time range for the calculation,

wherein storing the aggregative value and links includes storing a link to the calendar-data element in the fact-data element.

19. The method in accordance with claim 18, wherein storing a calendar-data element includes storing a calendar identifier, a calendar item identifier, a calendar item name, a start date, and an end date.

20. The method in accordance with claim 12, the method further comprising the steps of:

receiving a request identifying the fact-data element from the fact data structure after storing the fact-data element; and

outputting the aggregated value from the fact-data element.

21. The method in accordance with claim 20, wherein receiving a request identifying the fact-data element includes identifying the fact-data element using at least the measure-data element and the collection-data element.

22. The method in accordance with claim 21, wherein receiving a request includes receiving a request including a database cross-table operation having a join operation and a decode operation, such that each of the fact data structure, measure data structure, and collection data structure are each referenced during the request.

23. Computer-readable storage media having computer-executable instructions embodied thereon, wherein, when executed by at least one processor, the computer-executable instructions cause the processor to:

store a measure-data element in a measure data structure within a database;

store a collection-data element in a collection data structure within the database;

calculate an aggregated value from the database based at least in part on the measure-data element and the collection-data element, wherein the measure-data element defines how the aggregated value is calculated and the collection-data element defines a categorization of the aggregated value; and

store the aggregated value and links to the measure-data element and the collection-data element in a fact-data element of a fact data structure.

24. The computer-readable storage media in accordance with claim 23, wherein the computer-executable instructions cause the processor to:

store a calendar-data element in a calendar data structure within the database,

wherein calculating an aggregated value is based at least in part on the calendar-data element, wherein the calendar-data element defines a time range for the calculation,

wherein storing the aggregative value and links includes storing a link to the calendar-data element in the fact-data element.

25. The computer-readable storage media in accordance with claim 24, wherein the computer-executable instructions cause the processor to:

receive a request identifying the fact-data element from the fact data structure after storing the fact-data element; and

output the aggregated value from the fact-data element.

26. The computer-readable storage media in accordance with claim 25, wherein receiving a request includes identifying the fact-data element using at least the measure-data element, the calendar-data element, and the collection-data element.

27. The computer-readable storage media in accordance with claim 26, wherein receiving a request includes a database cross-table operation including a join operation and a decode operation, such that each of the fact data structure, measure data structure, calendar data structure, and collection data structure are each referenced during the request.