IP Library Granted Patent US 11,520,803
Granted Patent B1
US 11,520,803 · App. 16/417,943 · Granted Dec 6, 2022

Big-data view integration platform

Inventors: Sunitha Garapati (Normal, IL); Ryan M. Kroutil (Sugar Hill, GA); Brent Giosta (Bloomington, IL); Venu Madhav Valluri (Johns Creek, GA); Jennifer Pearsall (Bloomington, IL)
Assignee: State Farm Mutual Automobile Insurance Company
G06F16/26G06F3/0482G06F16/2465G06F16/254G06F16/287G06F2203/04803
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Quick Facts
Patent No.
US 11,520,803
App. No.
16/417,943
Granted
Dec 6, 2022
Kind
B1
Abstract

A big-data view integration platform generates integration guided user interfaces (GUIs). A first edge node ingests push-based and pull-based data from a plurality of platform services, which include legacy and non-legacy services having incompatible communication protocols. An event-based queue receives from the first edge node a plurality of queue events as indirect push-based data. A second set of queue events includes direct push-based data as received directly from a non-legacy platform service. A conformity component integrates the push-based data, the pull-based data, and the plurality of queue events into integration data having an enhanced integration format. A view integration component generates a plurality of data views from the integration data. A second edge node exposes the plurality of data views via an access services application programming interface (API). A new service execution component accesses the access services API to generate integration GUIs based on the data views.

Claims (52)

1. A tangible, non-transitory computer-readable medium storing instructions for generating a guided user interface (GUI), that when executed by one or more processors of a computing device, cause the computing device to:

receive, at an edge node of a big-data view integration platform, push-based data, pull-based data, and queue-based data from a plurality of platform services in a pre-determined time interval;

integrate, by the edge node and using a map-reduce process, the push-based data, the pull-based data, and the queue-based data into integration data having an enhanced integration format, wherein the integrating includes:

map-reducing the push-based data, the pull-based data, and the queue-based data to a plurality of sub files associated with a plurality of subjects;

filtering the integration data, based at least in part on the plurality of sub files, into a plurality of data views corresponding to the plurality of subjects; and

queuing the plurality of data views, according to the pre-determined time interval, in a database;

generate the GUI, the GUI including at least a first data view of the plurality of data views, and one or more selectable icons, each icon of the one or more selectable icons representing a respective incentive, wherein the GUI is configured to initiate a first asynchronous call via an application programming interface (API) to populate a first dynamic field with a second data view of the queued plurality of data views, the first dynamic field including a first icon of the one or more selectable icons representing a first incentive;

receive an update on the push-based data, the pull-based data, and the queue-based data associated with updated business plans of a plurality of business units, updated activities on the GUI, and updated user activities of users participating an incentive program;

update the queued plurality of data views in the database; and

receive a first selection of the first incentive on the GUI causing the GUI to initiate a second asynchronous call via the API to populate the second dynamic field with a third data view of the queued plurality of data views, the third data view including information indicative of the updated business plan, the updated activities on the GUI, and the updated user activities of the users participating the incentive program, and the second dynamic filed including a second icon of the one or more selectable icons representing a second incentive.

2. The tangible, non-transitory computer-readable medium of claim 1 , wherein the asynchronous call is an asynchronous JavaScript and extensible markup language (AJAX) based asynchronous call.

3. The tangible, non-transitory computer-readable medium of claim 1 , wherein the GUI is configured to generate a third dynamic field based on a second selection of the second incentive on the GUI causing the GUI to initiate a third asynchronous call to populate the third dynamic field with a fourth data view of the queued plurality of data views, the fourth data view including information indicative of the updated activities on the GUI, and the updated user activities of the users participating the incentive program during the pre-determined time interval.

4. The tangible, non-transitory computer-readable medium of claim 1 , wherein the GUI is dynamically generated.

5. The tangible, non-transitory computer-readable medium of claim 1 , wherein the one or more selectable incentives icons are restricted to certain end users.

6. The tangible, non-transitory computer-readable medium of claim 1 , wherein the GUI includes a visual interpretation of the integration data comprising at least one of:

comparisons of goals and actual results to the goals related to one or more users,

accomplished activities of the one or more users, or

business plans of a plurality of business units.

7. The tangible, non-transitory computer-readable medium of claim 1 , wherein the computing device is further caused to:

receive the update on the push-based data, the pull-based data, and the queue-based data associated with updated business plans of a plurality of business units, updated activities on the GUI, and the updated user activities of users participating the incentive program in the pre-determined time interval;

update the queued plurality of data views in the database in the pre-determined time interval; and

update the GUI in the pre-determined time interval.

8. The tangible, non-transitory computer-readable medium of claim 1 , wherein the GUI is generated in real-time.

9. The tangible, non-transitory computer-readable medium of claim 1 , wherein the GUI is generated in near real-time.

10. A big-data view integration method for generating a guided user interface (GUI), the big-data view integration method comprising:

receiving, at an edge node of a big-data view integration platform, push-based data, pull-based data, and queue-based data from a plurality of platform services;

integrating, by the edge node and using a map-reduce process, the push-based data, the pull-based data, and the queue-based data into integration data having an enhanced integration format, wherein the integrating includes:

map-reducing the push-based data, the pull-based data, and the queue-based data to a plurality of sub files associated with a plurality of subjects; and

generating the integration data based at least in part on the plurality of sub files, the integration data being indicative of a plurality of data views corresponding to the plurality of subjects; and

queuing the plurality of data views according to the pre-determined time interval in a database; and

generating the GUI including at least a first data view of the plurality of data views, the GUI including one or more selectable icons, each icon of the one or more selectable icons representing a respective incentive, wherein the GUI is configured to initiate a first asynchronous call via an application programming interface (API) to populate a first dynamic field with a second data view of the queued plurality of data views, the first dynamic field including a first icon of the one or more selectable icons representing a first incentive

receiving an update on the push-based data, the pull-based data, and the queue-based data associated with updated business plans of a plurality of business units, updated activities on the GUI, and updated user activities of users participating an incentive program;

updating the queued plurality of data views in the database; and

receiving a first selection of the first incentive on the GUI causing the GUI to initiate a second asynchronous call via the API to populate the second dynamic field with a third data view of the queued plurality of data views, the third data view including information indicative of the updated business plan, the updated activities on the GUI, and the updated user activities of the users participating the incentive program, and the second dynamic field including a second icon of the one or more selectable icons representing a second incentive.

11. The big-data view integration method of claim 10 , wherein the asynchronous call is an asynchronous JavaScript and extensible markup language (AJAX) based asynchronous call.

12. The big-data view integration method of claim 10 , wherein the GUI is configured to generate a third dynamic field based on a second selection of the second incentive on the GUI, the second selection causing the GUI to populate the third dynamic field with a fourth data view of the queued plurality of data views, the fourth data view including information indicative of the updated activities on the GUI, and the updated user activities of the users participating the incentive program during the pre-determined time interval.

13. The big-data view integration method of claim 10 , wherein the GUI is dynamically generated.

14. The big-data view integration method of claim 10 , wherein the one or more selectable incentives icons are restricted to certain end users.

15. The big-data view integration method of claim 10 , wherein the GUI includes a visual interpretation of the integration data comprising at least one of:

comparisons of goals and actual results to the goals related to one or more users,

accomplished activities of the one or more users, or

business plans of a plurality of business units.

16. The big-data view integration method of claim 10 , wherein the computing device is further caused to:

receive the update on the push-based data, the pull-based data, and the queue-based data associated with updated business plans of a plurality of business units, updated activities on the GUI, and the updated user activities of users participating the incentive program in the pre-determined time interval;

update the queued plurality of data views in the database in the pre-determined time interval; and

update the GUI in the pre-determined time interval.

17. The big-data view integration method of claim 10 , wherein the GUI is generated in real-time.

18. The big-data view integration method of claim 10 , wherein the GUI is generated in near real-time.

19. The big-data view integration method of claim 17 , wherein

the push-based data and the pull-based data are received from a first platform service utilizing a first communication protocol, and

the queue-based data is received from a first platform service and at least a second platform service utilizing a second communication protocol, the second communication protocol being different from the first communication protocol.

20. The big-data view integration method of claim 19 , wherein the enhanced integration format is different from formats of the push-based data, the pull-based data, and the queue-based data.

Assignments (2)
EMPLOYMENT AGREEMENT Recorded Jul 3, 2025
From: KROUTIL, RYAN
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 071878/0013 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 24, 2021
From: GARAPATI, SUNITHA; VALLURI, VENU MADHAV; GIOSTA, BRENT; PEARSALL, JENNIFER; KROUTIL, RYAN M.
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 056658/0373 →
Continuity (1)
Provisional Application 62731449 · Sep 14, 2018