Provenance tracking and quality analysis for revenue asset management data

• US 10,430,435 B2
• Filed: 03/15/2013
• Issued: 10/01/2019
• Est. Priority Date: 06/18/2012
• Status: Active Grant

• Current Assignee: Concentrix SREV Incorporated
• Original Assignee: Servicesource International Incorporated
• Inventors: Olsen, Greg, Bell, Ganesh, Craft, Ricardo, Thirunavukkarasu, Chellah, Subramanian, Lenin, Raghunath, Manohar, Chen, Zheng
• Primary Examiner(s): Masud, Rokib
• Application Number:
  US13/842,035
• Publication Number:
  US 20140114818A1
• Time in Patent Office: 2,391 Days
• Field of Search: 705 30
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination
• CPC Class Codes: G06F 16/24573 using data annotations, e.g. user-defined metadata
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 16/86 Mapping to a database
• CPC Class Codes: G06F 8/10 Requirements analysis; Specification techniques
• CPC Class Codes: G06F 8/20 Software design
• CPC Class Codes: G06F 8/60 Software deployment
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0264 based upon schedule
• CPC Class Codes: G06Q 30/0277 Online advertisement
• CPC Class Codes: G06Q 40/12 Accounting
• CPC Class Codes: H04L 63/10 for controlling access to devices or network resources

Abstract

In a recurring revenue management system, a first unit of data and a second unit of data is received. Content is extracted from the first unit of data and the second unit of data based on one or more parameters of a predefined data object that is part of an asset data model. The extracted content is added to an instance of the predefined data object, and a reference tag with identification information for its associated content is associated with the content extracted from each of the first unit of data and the second unit of data. A duplicate data condition can be detected and resolved by applying a predefined approach to conflict resolution based on the identification information in the reference tags of the content of the first unit of data and the second unit of data. Related methods, systems, and computer program products are also described.

Claims

1. A computer program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising:

receiving a first unit of data at a recurring revenue management system;

receiving a second unit of data at the recurring revenue management system;

extracting content from the first unit of data and the second unit of data based on one or more parameters of a predefined data object that is part of an asset data model defined in the recurring revenue management system;

adding the extracted content to an instance of the predefined data object and associating reference tags with the content extracted from each of the first unit of data and the second unit of data, each reference tag comprising identification information for its associated content, wherein the identification information of each reference tag comprises an indication of a source from which the associated extracted content was received, the source comprising one of a plurality of disparate data sources, the identification information further comprising a tag history including a history of previous reference tags that have been associated with the extracted content with which the reference tag is associated, the tag history configured to provide the history and source of origin of all changes to the associated extracted content;

detecting a duplicate data condition in which the content extracted from the first unit of data and the content extracted from the second unit of data provide redundant, conflicting values for a same field within the instance of the data object; and

resolving the duplicate data condition based on the indication of the source from which the associated extracted content was received and the history of previous reference tags that have been associated with the extracted content with which the reference tag is associated in the identification information of the reference tags.

2. The computer program product in accordance with claim 1, wherein resolving the duplicate data condition based on the indication of the source from which the associated extracted content was received and the history of previous reference tags that have been associated with the extracted content with which the reference tag is associated in the identification information of the reference tags comprises identifying one or more key fields in the content, each of the one or more key fields having a uniqueness property.

3. The computer program product in accordance with claim 1, wherein resolving the duplicate data condition based on the indication of the source from which the associated extracted content was received and the history of previous reference tags that have been associated with the extracted content with which the reference tag is associated in the identification information of the reference tags comprises a clustering algorithm to measure one or more statistical anomalies relative to a larger group of object in the asset data model.

4. The computer program product in accordance with claim 1, wherein the asset data model comprises one or more of each of product data objects, recurring revenue asset data objects, opportunity data objects, and contact data objects.

5. The computer program product in accordance with claim 4, wherein the content extracted from the first unit of data and the second unit of data represents one or more of each of product data, recurring revenue asset data, opportunity data, and contact data.

6. The computer program product in accordance with claim 1, wherein the operations further comprise generating an asset data object of a recurring revenue asset according to the resolving of the duplicate data condition.

7. The recurring revenue management system in accordance with claim 1, wherein the operations further comprise an operation to generate an asset data object of a recurring revenue asset according to the resolving of the duplicate data condition.

8. The computer program product of claim 1, wherein the plurality of disparate data sources comprises two or more of an entitlement system, an order management system, a pricing system, a product master database, a sales force automation system, a customer master database 216, or a contract management system.

20. The computer program product in accordance with claim 1, wherein each reference tag further comprises one or more of a date of receipt, a user identifier, and a permission level of a user who provided the extracted content.

9. A recurring revenue management system comprising:

at least one programmable processor; and

a machine-readable medium storing instructions that, when executed by the at least one processor, cause the at least one programmable processor to perform operations comprising;

receive a first unit of data;

receive a second unit of data;

extract content from the first unit of data and the second unit of data based on one or more parameters of a predefined data object that is part of an asset data model defined in the recurring revenue management system;

add the extracted content to an instance of the predefined data object and associating reference tags with the content extracted from each of the first unit of data and the second unit of data, each reference tag comprising identification information for its associated content, wherein the identification information of each reference tag comprises an indication of a source from which the associated extracted content was received, the source comprising one of a plurality of disparate data sources, the identification information further comprising a tag history including a history of previous reference tags that have been associated with the extracted content with which the reference tag is associated, the tag history configured to provide the history and source of origin of all changes to the associated extracted content;

detect a duplicate data condition in which the content extracted from the first unit of data and the content extracted from the second unit of data provide redundant, conflicting values for a same field within the instance of the data object; and

resolve the duplicate data condition based on the indication of the source from which the associated extracted content was received and the history of previous reference tags that have been associated with the extracted content with which the reference tag is associated in the identification information of the reference tags.

10. The recurring revenue management system in accordance with claim 9, wherein resolving the duplicate data condition based on the indication of the source from which the associated extracted content was received and the history of previous reference tags that have been associated with the extracted content with which the reference tag is associated in the identification information of the reference tags comprises identifying one or more key fields in the content, each of the one or more key fields having a uniqueness property.

11. The recurring revenue management system in accordance with claim 9, wherein resolving the duplicate data condition based on the indication of the source from which the associated extracted content was received and the history of previous reference tags that have been associated with the extracted content with which the reference tag is associated in the identification information of the reference tags comprises a clustering algorithm to measure one or more statistical anomalies relative to a larger group of object in the asset data model.

12. The recurring revenue management system in accordance with claim 9, wherein the asset data model comprises one or more of each of product data objects, recurring revenue asset data objects, opportunity data objects, and contact data objects.

13. The recurring revenue management system in accordance with claim 12, wherein the content extracted from the first unit of data and the second unit of data represents one or more of each of product data, recurring revenue asset data, opportunity data, and contact data.

14. A computer-implemented method comprising:

receiving, by one or more processors, a first unit of data related to a recurring revenue asset;

receiving, by the one or more processors, a second unit of data related to the recurring revenue asset;

extracting, by the one or more processors, content from the first unit of data and the second unit of data based on one or more parameters of a predefined data object that is part of an asset data model defined in a recurring revenue management system for the recurring revenue asset;

adding the extracted content to an instance of the predefined data object and associating reference tags with the content extracted from each of the first unit of data and the second unit of data, each reference tag comprising identification information for its associated content, wherein the identification information of each reference tag comprises an indication of a source from which the associated extracted content was received, the source comprising one of a plurality of disparate data sources, the identification information further comprising a tag history including a history of previous reference tags that have been associated with the extracted content with which the reference tag is associated, the tag history configured to provide the history and source of origin of all changes to the associated extracted content;

detecting, by the one or more processors, a duplicate data condition in which the content extracted from the first unit of data and the content extracted from the second unit of data provide redundant, conflicting values for a same field within the instance of the data object; and

resolving, by the one or more processors, the duplicate data condition indication of the source from which the associated extracted content was received and the history of previous reference tags that have been associated with the extracted content with which the reference tag is associated in the identification information of the reference tags.

15. The computer-implemented method in accordance with claim 14, wherein resolving the duplicate data condition based on the indication of the source from which the associated extracted content was received and the history of previous reference tags that have been associated with the extracted content with which the reference tag is associated in the identification information of the reference tags comprises identifying one or more key fields in the content, each of the one or more key fields having a uniqueness property.

16. The computer-implemented method in accordance with claim 14, wherein resolving the duplicate data condition based on the indication of the source from which the associated extracted content was received and the history of previous reference tags that have been associated with the extracted content with which the reference tag is associated in the identification information of the reference tags comprises a clustering algorithm to measure one or more statistical anomalies relative to a larger group of object in the asset data model.

17. The computer-implemented method in accordance with claim 14, wherein the asset data model comprises one or more of each of product data objects, recurring revenue asset data objects, opportunity data objects, and contact data objects.

18. The computer-implemented method in accordance with claim 17, wherein the content extracted from the first unit of data and the second unit of data represents one or more of each of product data, recurring revenue asset data, opportunity data, and contact data.

19. The computer-implemented method in accordance with claim 14, wherein the operations further comprise generating, by the one or more processors, an asset data object of a recurring revenue asset according to the resolving of the duplicate data condition.