System and method for enriching and normalizing data

US11556510B1 · kind B1 · utility

Assignee

• KPMG LLP · US

Inventors

• Niels Hanson · Seattle, US
• James Johnson Gardner · Harbor Hills, US
• Punit S. Orpe · Mahwah, US
• Wendy Du · Anaheim, US
• Laurence Anthony BROWN · Dallas, US
• Ranjan Vivek Mannige · Atlanta, US
• David John Green · Malvern, GB
• Michael Ahn · Weilheim, DE
• Yang Zhou · Nanhu, CN
• Andrew Yuan · New York, US
• Adam Helio Rosa · Longmont, US
• Kyle B. Chen · Chicago, US
• Alex Perusse · Seattle, US
• Christian Alexander Manaog · Queens, US
• Yeshwanth Somu · Arlington, US
• Xin Cheng · Seattle, US
• Torey C. Bearly · Renton, US
• Raghav Saboo · New York, US
• Sphoorthy Pamaraju · Secaucus, US
• Erik Ernst · Denver, US
• Can Ozuretmen · Atlanta, US
• Yuan Zhang · Wuxi, CN

Key dates

• Filing date: Feb 18, 2022
• Grant date: Jan 17, 2023
• Expiry date: Feb 18, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06F16/254
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

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.