Data quality issues emerge from multiple failure points from development practices to production life cycle, each compounding ...

The data purgatory hits major technology initiatives like AI projects when obstacles are created by data accuracy, quality, and accessibility. Fast Company has put a spotlight on the make-or-break ...

It’s no longer how good your model is, it’s how good your data is. Why privacy-preserving synthetic data is key to scaling AI. The potential of generative AI has captivated both businesses and ...

Holy Scripture and the capital markets seldom intersect, but the struggle for high-quality data within the private markets is reminiscent of the proverb, “In the land of the blind, the one-eyed man is ...

Everyone understands data is important, but many business leaders don’t realize how impactful data quality can be on day-to-day operations. In my experience, nearly all process breakdowns have root ...

Infogix, a leading provider of data management tools and a pioneer in data integrity, debunked seven popular data quality myths that are doing businesses more harm than good. According to a recent ...

As the push to integrate artificial intelligence and increase interoperability evolves, Clinical Architecture sees a dire need for tools that can assess the quality of healthcare data. Poor quality ...

Data quality is the top barrier to AI in revenue cycle management, according to a report from Black Book Research. Black Book surveyed 149 revenue cycle leaders between Nov. 1-11 to examine how ...

In this episode of Need to Know, our series covering the topics and issues influencing markets and the global conversation, Michael Beal, Co-Head of Enterprise Data Science at Bloomberg, discusses the ...