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 ...

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 ...

Top-notch data operations are essential for enhanced decision-making, operational efficiency, and fueling AI. Here’s how IT leaders are evolving their data management strategies to make the most of ...

Sandesh Gawande, with 29+ years of experience in data and CEO of iceDQ: We engineer data reliability, because quality is never an accident. Organizations are investing heavily in AI and big data ...

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 ...

AI investments are being built on flawed data as business leaders struggle to make quality a priority. 81% of AI professionals say their company still has significant data quality issues, yet 85% ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

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 ...

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 ...