The old "garbage in, garbage out" adage has never gone out of style. The ravenous appetite for data on the part of analytics and machine learning models has elevated the urgency to get the data right.

Strong data quality checks reduce bias, drift and inconsistencies that can distort analytics and AI outcomes before datasets reach production.

SAN FRANCISCO--(BUSINESS WIRE)--Bigeye, the creators of the leading data observability platform, today announced the full schedule for the Data Reliability Engineering Conference 2022 (DRE-Con), ...

Belgium-based data observability firm Soda Data NV today announced the launch of Soda Core, an open-source framework that it says can be used to embed reliability checks and quality management into ...

SAN FRANCISCO--(BUSINESS WIRE)--Monte Carlo, the data observability company, today announced Data Reliability Dashboard, a new functionality to help customers better understand and communicate the ...

From streaming and ridesharing to smart factories and virtual assistants, the modern world has been defined by the rapid development of connected technologies. Underpinning this shift to a ...

SAN FRANCISCO, Dec. 01, 2021 (GLOBE NEWSWIRE) -- Bigeye, the creator of the leading data observability platform, announces the Data Reliability Engineering Conference (DRE-CON), to be held virtually ...

Consumer Reports receives a wide range of questions from enthusiasts and the auto industry looking for a deeper understanding of the methodology used in the reliability section of our latest Annual ...