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 ...

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 ...

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.

Data quality issues emerge from multiple failure points from development practices to production life cycle, each compounding others in ways that are detected only at the end: Improper data testing ...

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, ...

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 ...

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 ...

The following article was written by Ann O’Neill, RN, MBA/HCM, director of clinical operations for Regent Surgical Health.By now, almost everyone in the ASC industry is aware of the new CMS quality ...

eSyM: An Electronic Health Record–Integrated Patient-Reported Outcomes–Based Cancer Symptom Management Program Used by Six Diverse Health Systems The Medicare Access and CHIP Reauthorization Act of ...

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