Data-driven decisions require data that is trustworthy, available, and timely. Upping the dataops game is a worthwhile way to offer business leaders reliable insights. Measuring quality of any kind ...

Learn the definition of data quality and discover best practices for maintaining accurate and reliable data. Data quality refers to the reliability, accuracy, consistency, and validity of your data.

Zehra Cataltepe is the CEO of TAZI.AI, an adaptive, explainable AI and GenAI platform for business users. She has 100+ AI papers & patents. In many industries, including banking, insurance and ...

Performance measurement – if done right – can be a core activity to move the health care system to higher value for the American public, while rewarding health professionals and health care ...

Back in 2006, British mathematician Clive Humby stated that data was the new oil. Like oil, data isn’t useful in its raw state and must be refined, processed, and distributed to deliver value. Nearly ...

Amidst ever-changing regulatory requirements and hype around the potential of data-driven technologies, demand for better quality data in the financial industry has never been higher. Stuart Harvey, ...

AI is powerful, but it is not magic. Just because developers use AI tools does not mean outcomes will improve automatically.

Understandably, the need for clearly defined accountable care organization clinical outcomes criteria has led to industry-wide interpretation. But while stakeholder interest lies in shared savings and ...

Without quality control, even expensive, high-precision radiometers can generate misleading data, according to Solargis' ...

There exist many opportunities for vendors in the data quality space to create tools that cover a broader scope, yet many of those opportunities remain untapped, according to an analyst. Andy Hayler, ...