Universal analytical data mart and data structure for same

• US 10,628,456 B2
• Filed: 08/04/2016
• Issued: 04/21/2020
• Est. Priority Date: 10/30/2015
• Status: Active Grant

• Current Assignee: Hartford Fire Insurance Company (The Hartford Financial Services Group, Inc.)
• Original Assignee: Hartford Fire Insurance Company (The Hartford Financial Services Group, Inc.)
• Inventors: Beznos, Vladislav Michael, Clark, Lynne C., Drennan, III, Arthur Paul, Kuethman, David J., Lewis, William C., Robinson, Fred A.
• Primary Examiner(s): Thai, Hanh B
• Application Number:
  US15/228,739
• Publication Number:
  US 20170124176A1
• Time in Patent Office: 1,356 Days
• Field of Search: 707751, 707726
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06Q 20/102 Bill distribution or payments
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

A device and method are described for a universal analytical data mart and data structure for same. The analytical data mart (ADM) associated data structure is designed to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis. Conceptually, the ADM enables analytics and business intelligence from multiple frames of reference including people, such as parties and actors including individuals and organizations, places, such as addresses with geographic information at various levels of view, objects, such as insured properties, automobiles and machinery, and events, milestones which happen at points in time and provide analytical/business value.

Claims

1. A system to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis, the system comprising:

a plurality of different data sources providing data including a plurality of data points stored in a plurality of storage devices;

at least one processor for processing data from each of the plurality of different data sources by processing dimensional and fact attributes from each of the plurality of data points wherein the fact attributes are measurable attributes of the data points and the dimensional attributes are descriptors of the fact attributes; and

a database for storing the processed dimensional and fact attributes from each of the plurality of data points as data in tables in a datamart and linking the fact attributes back to the provided data including the plurality of data points from the plurality of different data sources,

wherein the data in the datamart provides multiple frames of reference including at least two of people, places, objects, and events by accessing a fact table for one of the multiple frames of reference by providing access to the dimensional tables providing descriptors to the accessed fact table and access the linked provided data including the plurality of data points.

2. The system of claim 1 further comprising determining at least one metric for at least one of the fact attributes and storing the at least one metric with the at least one of the fact attributes in the fact table.

3. The system of claim 1 wherein the processing of the dimensional attributes includes generating an anchor identification for providing a key to link the dimensional attribute to the described related fact.

4. The system of claim 3 wherein the dimensional attributes are processed with Astage processing.

5. The system of claim 1 wherein a plurality of pointers are created from the processing fact attributes, the plurality of pointers linking ones of the fact attributes back to the provided data.

6. The system of claim 1 wherein people include parties and actors, wherein objects include insured properties, automobiles and machinery, wherein events include milestones which happen at points in time, and wherein places include addresses with geographic information.

7. The system of claim 6 wherein the geographic information is at various levels of view.

8. The system of claim 1 wherein the at least two of people, places, objects, and events provide analytical/business value.

9. The system of claim 1 wherein the data is stored in at least one of a data warehouse, received via a third party interface, and data stored in a data lake.

10. The system of claim 1 wherein the fact attribute is a payment amount and the dimensional attribute is the payment type.

11. The system of claim 1 wherein the fact attributes and dimensional attributes are processed and linked using at least one extract transform and load process.

12. A method for integrating data from disparate sources enabling analysis of the integrated data from multiple perspectives, the method comprising:

storing data from a plurality of different data sources including a plurality of data points in a plurality of storage devices;

processing data points from each of the plurality of different data sources by processing dimensional and fact attributes from each of the plurality of data points wherein the fact attributes are measurable attributes of the data points and the dimensional attributes are descriptors of the fact attributes;

storing the processed dimensional and fact attributes from each of the plurality of data points as data in tables in a datamart; and

linking the fact attributes back to the provided data including the plurality of data points from the plurality of different data sources, wherein the data in the datamart provides multiple frames of reference including at least two of people, places, objects, and events by accessing a fact table for one of the multiple frames of reference by providing access to the dimensional tables providing descriptors to the accessed fact table and access the linked provided data including the plurality of data points.

13. The method of claim 12 wherein the processing of dimensional attributes includes reformatting the dimensional attribute to a common format, comparing the reformatted dimensional attribute and creating an anchor identification, performing Astage processing and combining alike entities.

14. The method of claim 12 wherein the processing of fact attributes includes reformatting the fact attribute, picking an identification population and generating an identifier, performing Astage processing and combining alike entities.

15. The method of claim 12 wherein the at least two of people, places, objects, and events provide analytical/business value.

16. The method of claim 12 wherein the fact attribute is a payment amount and the dimensional attribute is the payment type.

17. The method of claim 12 wherein the fact attributes and dimensional attributes are processed and linked using at least one extract transform and load process including Astage processing and generating anchor identification.

18. A system to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis, the system comprising:

a plurality of different data sources providing data including a plurality of data points stored in a plurality of storage devices;

at least one processor for processing data from each of the plurality of different data sources by processing dimensional and fact attributes from each of the plurality of data points wherein the fact attributes are measurable attributes of the data points and the dimensional attributes are descriptors of the fact attributes; and

a database for storing the processed dimensional and fact attributes from each of the plurality of data points as data in tables in a datamart,

wherein the data in the datamart provides multiple frames of reference including at least two of people, places, objects, and events by accessing a fact table for one of the multiple frames of reference.

19. The system of claim 18 wherein the processing of the dimensional attributes includes generating an anchor identification for providing a key to link the dimensional attribute to the described related fact.

20. The system of claim 18 wherein a plurality of pointers are created from the processing fact attributes, the plurality of pointers linking ones of the fact attributes back to the provided data.