Capital One Services, LLC

Rees Draminski

Matthew Louis Nowak

Narender Pashikant

David Walter Peters

Maqbool A Khatri

Kelvin Wong

James C McGRORY

Justin Cheng

Sean O'neill

Alan Christopher Weaver

In some implementations, a data quality system may receive an incoming data set for data quality analysis. The data quality system may obtain data quality validation information from one or more data repositories that form a data quality knowledge base. The data quality system may use one or more machine learning models to evaluate whether the incoming data set has one or more anomalies based on the data quality validation information. The data quality system may generate data quality results for the incoming data set based on an output from the one or more machine learning models. The data quality system may update the data quality knowledge base in accordance with the data quality results for the incoming data set.

Artificial intelligence system for data quality resolution

Growing community of inventors

Vienna, VA, United States of America

Rees Draminski