Engine to propagate data across systems

Patent metadata

Field	Value
Publication number	US-11528341-B2
Application number	US-202117533351-A
Country	US
Kind code	B2
Filing date	Nov 23, 2021
Priority date	Mar 4, 2020
Publication date	Dec 13, 2022
Grant date	Dec 13, 2022

Abstract

Aspects of the disclosure relate to cognitive automation-based engine processing to propagate data across multiple systems via a private network to overcome technical system, resource consumption, and architecture limitations. Data to be propagated can be manually input or extracted from a digital file. The data can be parsed by analyzing for correct syntax, normalized into first through sixth normal forms, segmented into packets for efficient data transmission, validated to ensure that the data satisfies defined formats and input criteria, and distributed into a plurality of data stores coupled to the private network, thereby propagating data without repetitive manual entry. The data may also be enriched by, for example, correcting for any errors or linking with other potentially related data. Based on data enrichment, recommendations of additional target(s) for propagation of data can be identified. Reports may also be generated. The cognitive automation may be performed in real-time to expedite processing.

First claim

What is claimed is:

1. A method for propagating data across multiple systems via a private network to avoid repetitive data entry by a user, the method comprising the steps of:
a. receiving, by a platform from a data source, input source data;
b. storing, by the platform in a first sector of computer-readable media, the input source data;
c. extracting in real-time, by the platform from the input source data in the first sector of the computer-readable media, data to be propagated;
d. storing in real-time, by the platform in a second sector of the computer-readable media, the data to be propagated;
e. parsing in real-time, by the platform, the data to be propagated into parsed data;
f. storing in real-time, by the platform in a fourth sector of the computer-readable media, the parsed data;
g. normalizing in real-time, by the platform, the parsed data into normalized data for efficient processing, said normalized data normalized into at least a first normal form;
h. storing in real-time, by the platform in a fifth sector of the computer-readable media, the normalized data;
i. segmenting in real-time, by the platform, the normalized data into segmented data by breaking the normalized data into a plurality of smaller packets for efficient data transmission;
j. storing in real-time, by the platform in a sixth sector of the computer-readable media, the segmented data;
k. validating in real-time, by the platform, the segmented data into validated data to ensure that the validated data satisfies defined formats and input criteria;
l. storing in real-time, by the platform in a seventh sector of the computer-readable media, the validated data; and
m. distributing in real-time, by the platform over the private network, the validated data into a plurality of data stores communicatively coupled to the private network, thereby propagating said validated data without repetitive data entry.

2. The method of claim 1 further comprising the steps of:
a. enriching in real-time, by the platform, the validated data to enriched data that is corrected for any errors; and
b. storing in real-time, by the platform in an eighth sector of the computer-readable media, the enriched data.

3. The method of claim 2 further comprising the steps of:
a. generating in real-time, by the platform, a recommendation of at least one additional target in which the enriched data may be stored;
b. storing in real-time, by the platform in a ninth sector of the computer-readable media, the recommendation of said at least one additional target in which the enriched data may be stored;
c. transmitting in real-time, by the platform over the private network, the recommendation; and
d. storing, by the platform, the enriched data in the at least one additional target if approved.

4. The method of claim 3 wherein the data to be propagated into said parsed data by analyzing the data to be propagated for correct syntax.

5. The method of claim 4 wherein the parsed data is normalized by breaking the parsed data into record groups for efficient processing.

6. The method of claim 5 wherein the input source data is a digital file.

7. The method of claim 5 wherein the digital file comprises unstructured data.

8. The method of claim 6 wherein the input source data is generated by scanning the digital file.

9. The method of claim 8 wherein the validation of the segmented data into said validated data is validated by forecast validation based on prognostic output from at least one numerical model.

10. The method of claim 8 wherein the validation of the segmented data into said validated data is validated by regression validation by determine whether an output of a regression model is adequate.

11. The method of claim 8 wherein the validation of the segmented data into said validated data is validated by statistical model validation to determine with outputs of a statistical model are acceptable.

12. The method of claim 8 wherein the validation of the segmented data into said validated data is validated by documenting that a process meets predetermined specifications and fulfills an intended purpose.

13. The method of claim 8 wherein the validation of the segmented data into said validated data is validated by checking whether segmented data follows a defined structure.

14. A method for propagating data across multiple systems via a private network to avoid repetitive data entry by a user, the method comprising the steps of:
a. receiving, by a platform from a data source, input source data;
b. storing, by the platform in a first sector of computer-readable media, the input source data;
c. extracting in real-time, by the platform from the input source data in the first sector of the computer-readable media, data to be propagated;
d. storing in real-time, by the platform in a second sector of the computer-readable media, the data to be propagated;
e. parsing in real-time, by the platform, the data to be propagated into parsed data;
f. storing in real-time, by the platform in a fourth sector of the computer-readable media, the parsed data;
g. normalizing in real-time, by the platform, the parsed data into normalized data for efficient processing, said normalized data normalized into at least a first normal form;
h. storing in real-time, by the platform in a fifth sector of the computer-readable media, the normalized data;
i. segmenting in real-time, by the platform, the normalized data into segmented data by breaking the normalized data into a plurality of smaller packets for efficient data transmission;
j. storing in real-time, by the platform in a sixth sector of the computer-readable media, the segmented data;
k. validating in real-time, by the platform, the segmented data into validated data to ensure that the validated data satisfies defined formats and input criteria;
l. storing in real-time, by the platform in a seventh sector of the computer-readable media, the validated data;
m. enriching in real-time, by the platform, the validated data to enriched data that is corrected for any errors; and
n. storing in real-time, by the platform in an eighth sector of the computer-readable media, the enriched data.

15. The method of claim 14 further comprising the steps of:
a. generating in real-time, by the platform, a recommendation of at least one additional target in which the enriched data may be stored;
b. storing in real-time, by the platform in a ninth sector of the computer-readable media, the recommendation of said at least one additional target in which the enriched data may be stored;
c. transmitting in real-time, by the platform over the private network, the recommendation; and
d. storing, by the platform, the enriched data in the at least one additional target if approved.

16. The method of claim 15 further comprising the step of distributing in real-time, by the platform over the private network, the validated data into a plurality of data stores communicatively coupled to the private network, thereby propagating said validated data without repetitive data entry.

17. The method of claim 16 wherein the data to be propagated into said parsed data by analyzing the data to be propagated for correct syntax.

18. The method of claim 17 wherein the parsed data is normalized by breaking the parsed data into record groups for efficient processing.

19. A method for propagating data across multiple systems via a private network to avoid repetitive data entry by a user, the method comprising the steps of:
a. receiving, by a platform from a da

Assignees

• Bank Of America

Inventors

• Ogrinz Michael
• Black Christine D
• Varma Jayachandra
• Kim Jinna

Classifications

• G06N5/04

  Inference or reasoning models · CPC title

• H04L67/10 Primary

  in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46) · CPC title

• H04L67/01

  Protocols · CPC title

• H04L47/2416

  Real-time traffic · CPC title

• H04L2012/5621

  Virtual private network [VPN]; Private-network - network-interface (P-NNI) · CPC title