Method, process and system to atomically structure varied data and transform into context associated data

• US 8,892,513 B2
• Filed: 07/31/2012
• Issued: 11/18/2014
• Est. Priority Date: 10/31/2011
• Status: Active Grant

• Current Assignee: u9t, Inc.
• Original Assignee: u9t, Inc.
• Inventors: Forsythe, Hamish
• Primary Examiner(s): Fleurantin, Jean B
• Assistant Examiner(s): Sultana, Nargis
• Application Number:
  US13/563,697
• Publication Number:
  US 20130110775A1
• Time in Patent Office: 840 Days
• Field of Search: 707/613
• US Class Current: 707/613
• CPC Class Codes: G06F 16/21 Design, administration or maintenance of databases
• CPC Class Codes: G06F 16/273 Asynchronous replication or reconciliation
• CPC Class Codes: G06F 16/90 Details of database functions independent of the retrieved data types

Abstract

A novel method, system and process for the enterprise software are described. The data is created, captured, ingested, stored, atomized, monitored, separated, analyzed, enriched, correlated, managed, automated, processed, isolated, secured and synthesized (for example published or automatically pushed to user). The data is recreated using automated contextual delivery methods and processes. This process enables a user to regulate the industry wide leading practices and constantly enrich data. Task allocation is automated. This SaaS and/or Cloud computing system may be installed and distributed across users'"'"' device, public cloud, behind a company'"'"'s firewall and/or additional security may be provided using privacy vault. This method, system and process for this software may be implemented on a machine readable media.

Claims

1. A computer-implemented method of data management, comprising:

recognizing of a natural structure, relationship, association and correlations within a data present in a given environment as a content data, wherein the content data is a combination of an atomized data, a reconfigured data and a new data, wherein the data management is an enterprise data management;

capturing the content data and a context of the content data and a relevant external data residing as at least one of an internal data and relevant external data;

running a layered asynchronous context enrichment software on a machine-readable medium on the content data, internal data and relevant external data present in the given environment to transform as an atomized grain by ingesting the content data, internal data and relevant external data present in the given environment and atomizing at a lower and higher level for preliminary correlation;

evaluating and enriching the atomized grain dynamically and asynchronously based on a contextual content and adding value by correlating the atomized grain to create an atomized and correlated data;

segmenting the content data, relevant data and atomized and correlated data based on predefined rules for security and dividing them into a sensitive and non-sensitive data;

storing the content data, relevant external data and atomized and correlated data, sensitive data and non-sensitive data in at least one of a same location and different location in a data storage;

retrieving a reconfigured data from the database to present to a user as the new data;

dynamically annotating using layered asynchronous context enrichment software on the new data and presenting to the user based on a budget and rule constraint; and

presenting the new data to the user after meeting the budget and rule constraint to the user.

2. The method of data management as in claim 1, wherein

reconfiguring the content data, relevant external data and atomized and correlated data, sensitive data and non-sensitive data using layered asynchronous context enrichment software is done to create the reconfigured data;

and

storing the reconfigured data in the data storage.

3. The method of data management as in claim 1, further comprising:

allocating the atomized grain identified by the layered asynchronous context enrichment software as a task to a talent present in the company to fulfill the task;

updating the availability of the talent based on a time, expertise and success rate for the particular atomized grain; and

selecting the talent as the best for the task and updating the data in the data storage.

4. The method of data management as in claim 1, further comprising:

ingesting a data input by the user using layered asynchronous context enrichment software to determine an atomized grain size, wherein the atomized grain size is at least one of a single character, word, a sentence, a paragraph, a cell in excel spread sheet, a row, a social media chat, a sequence of video or audio.

5. The method of data management as in claim 1, further comprising:

incorporating the new data using layered asynchronous context enrichment software into the given environment as the content data;

dynamically adding value using layered asynchronous context enrichment software to the atomized and correlated data, reconfigured data, new data and content data; and

presenting the cyclically processed content data, atomized and correlated data, reconfigured data and new data as a content data to the user in real time.

6. The method of data management as in claim 5, further comprising:

storing the cyclically processed content data, atomized and correlated data, reconfigured data and new data as a content data to the user in real time.

7. The method of data management as in claim 6, further comprising:

running the layered asynchronous context enrichment software at a multi-layer level, wherein the multi-layer level is at least one of a firmware, hardware and software layer while creating the content data, atomized and correlated data, reconfigured data and new data.

8. The method of data management as in claim 1, further comprising:

distributing the new data to at least one of a team, group, individual and an expert as a task for adding value within the enterprise;

monitoring the progress of the task on the new data allocated to the team, group, individual and expert within the enterprise in real time; and

updating the new data using layered asynchronous context enrichment software after value addition as the content data in the enterprise.

9. The method of data management as in claim 8, further comprising:

running the layered asynchronous context enrichment software at least one of a firmware, hardware and software layer and creating a value added data.

10. The method of data management as in claim 9, further comprising:

securing the content data and the value added data created by at least one of a firmware, hardware and software layer.

11. The method of data management as in claim 10, wherein the content data is at least one of a structured data, semi-structured and unstructured data.

12. The method of data management as in claim 11, further comprising:

complying with existing business process constraints and rules in the enterprise while creating the value added data at the enterprise level.

13. The method of data management as in claim 12, further comprising:

dynamically updating the content data to the value added data which is discoverable and editable.

14. The method of data management as in claim 13, wherein the content data is at least one of financial data, marketing data, insurance data, project data, sales data, service and support data, social data, raw data, consumer data, entertainment data, scientific data and health care data.

15. The method of data management as in claim 14, further comprising:

organizing and structuring the content data and the value added data for multiple department based on relevance;

delivering the content data and value added data to the appropriate individuals in an enterprise system.

16. The method of data management as in claim 15, further comprising:

prioritizing the content data and value added data based on a governance, compliance, budget and rule constraint.

17. The method of data management as in claim 16, wherein the rule constraint is at least one of a version control for the content data and value added data and number of iteration the layered asynchronous context enrichment software should run on content data and value added data.

18. A system for data management, comprising:

a user interface;

a non-transitory machine-readable media to run a layered asynchronous context enrichment software at multiple layer for an enterprise wide system; and

one or more processors in at least one of a firmware, hardware and software layer to execute the layered asynchronous context enrichment software coupled to the user interface, the system for data management configured to;

run a layered asynchronous context enrichment software on the content data, internal data and relevant external data present in the given environment to transform as an atomized grain by ingesting the content data, internal data and relevant external data present in the given environment and atomizing at a lower and higher level for preliminary correlation and creating a value added data;

evaluate and enrich the atomized grain dynamically and asynchronously based on a contextual content and adding value by correlating the atomized grain to create an atomized and correlated data;

segment the content data, relevant data and atomized and correlated data based on predefined rules for security and dividing them into a sensitive and non-sensitive data;

retrieve the reconfigured data from the database to present to a user as the new data;

dynamically annotate using layered asynchronous context enrichment software on the new data and presenting it to the user based on a budget and rule constraint; and

present the new data to the user after meeting the budget and rule constraint to the user.

19. The system of data management of claim 18, further comprising:

a database to store a content data and value added data that was dynamically created; and

a secure network to gather a content data, an internal data and a relevant external data, wherein the content data is a combination of an atomized data, a reconfigured data and a new data, wherein the system data management is an enterprise system data management.

20. The system of data management of claim 19, further comprising:

monitor the progress of the task on the new data allocated to the team, group, individual and expert within the enterprise in real time; and

update the new data using layered asynchronous context enrichment software after value addition as the content data in the enterprise wide system.

21. The system of data management of claim 20, further comprising:

harvest context from varied data, external data and internal data to correlate data.