The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jan. 17, 2023
Filed:
Feb. 18, 2022
Kpmg Llp, New York, NY (US);
Niels Hanson, Seattle, WA (US);
James Johnson Gardner, Rolling Hills Estates, CA (US);
Punit S. Orpe, Mahwah, NJ (US);
Wendy Du, Anaheim, CA (US);
Laurence Anthony Brown, Dallas, TX (US);
Ranjan Vivek Mannige, Atlanta, GA (US);
David Green, Evanston, IL (US);
Michael Ahn, Burke, VA (US);
Yang Zhou, Dallas, TX (US);
Andrew Yuan, New York, NY (US);
Adam Helio Rosa, Longmont, CO (US);
Kyle B. Chen, Chicago, IL (US);
Alex Perusse, Seattle, WA (US);
Christian Alexander Manaog, Rego Park, NY (US);
Yeshwanth Somu, Arlington, VA (US);
Xin Cheng, Seattle, WA (US);
Torey C. Bearly, Renton, WA (US);
Raghav Saboo, New York, NY (US);
Sphoorthy Pamaraju, Secaucus, NJ (US);
Erik Ernst, Denver, CO (US);
Can Ozuretmen, Atlanta, GA (US);
Yuan Zhang, Cincinnati, OH (US);
KPMG LLP, New York, NY (US);
Abstract
An integrated platform system that employ a series of machine learning techniques and prediction and detection units that can process input data and extract and generate meaningful insights and predictions therefrom. The system integrates together multiple different data storage types and applications that generates data of different types, and an associated processing system for processing the different data types, store the data in a common data model to normalize the data, determine the data lineage of the data, and then process the data using different types of techniques. The data can also be processed by a prediction unit for generating meaningful insights and predictions or by an anomaly detection unit for detecting one or more anomalies in the data.