System and method for a big data analytics enterprise framework

• US 10,643,181 B2
• Filed: 08/18/2015
• Issued: 05/05/2020
• Est. Priority Date: 08/18/2015
• Status: Active Grant

• Current Assignee: MA FOI Analytics and Business Services Private Limited
• Original Assignee: MA FOI Analytics and Business Services Private Limited
• Inventors: Ayyaswami, Satish
• Primary Examiner(s): Huang, Cheng-Feng
• Application Number:
  US14/828,518
• Publication Number:
  US 20170053242A1
• Time in Patent Office: 1,722 Days
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 8/20 Software design
• CPC Class Codes: G06F 8/34 Graphical or visual programming
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06Q 10/103 Workflow collaboration or project management
• CPC Class Codes: H04L 63/105 Multiple levels of security

Abstract

A method and system for providing big data analytics framework for predictive and qualitative analysis for application developers, data scientists and system engineers without having technology specific programming experience. Further the framework contains adapters for the software engineers to configure the big data hub, wherein these software engineers can easily share, store, process and predict functionalities with the data scientists and user interface (UI) developers.

Claims

1. A method for providing big data analytics, the method comprising steps of:

providing a web-based explorer interface module to receive a database schema of a source database, wherein the database schema indicates how entities that make up a database relate to one another;

configuring a pre-defined or custom based adapter module, which programmatically refers to the database schema defined using the web-based explorer interface module, to retrieve data from the source database of said database schema and ingest the retrieved data into a target database;

providing a processor manager module configured to process the ingested data to obtain metrics, wherein the processing is based on how the metrics are defined;

providing a predict manager module configured to assign an analytic task to a data scientist, wherein the data scientist uses a curl tool to pull said ingested data via REST (Representational State Transfer) architectural style APIs, and once the ingested data is built, the data scientist deploys a scoring engine using the curl tool; and

providing a user interface module configured to provide visualization of the ingested data, in the form of charts;

wherein the modules are coupled with a framework and integrated for ad-hoc big data gathering.

2. The method of claim 1, wherein the database schema is stored in form of structured and unstructured big data.

3. The method of claim 1, wherein each of the modules is created, tested initiated, stopped, restarted upgraded, modified, deleted, deployed, and un-deployed based on the request from application developers or software engineers or data scientists or business user.

4. The method of claim 1, wherein the framework is equipped with monitoring, management and control of service setup, software and hardware setup implemented by means of web-based portals in the framework.

5. The method of claim 1, wherein the framework is configured to enable identity management, policy driven access control, data privacy controls and authentication of various levels accessing the framework.