To establish a consistent approach to assess, manage and improve data quality across the data lifecycle, covering a wide spectrum of data types, and taking into account the blurred line between data ...

An article recently published in Nature proposes a new way to evaluate data quality for artificial intelligence used in healthcare. Several documentation efforts and frameworks already exist to ...

Data quality problems are systemic in agriculture, the researchers note. Historical reliance on local practices, fragmented ...

We developed a framework of five data quality dimensions (DQD; completeness, concordance, conformance, plausibility, and temporality). Participants signed a consent and Health Insurance Portability ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Data quality, a subset of data intelligence, is a topic that many ...

PITTSBURGH--(BUSINESS WIRE)--CMMI ® Institute has announced public availability of the Patient Demographic Data Quality (PDDQ) framework, developed in partnership with the US Department of Health and ...

Unlock the power of your data with an effective data governance framework for security, compliance, and decision-making. Data governance frameworks are structured approaches to managing and utilizing ...

After years of experimentation, AI adoption is at the forefront of enterprise strategies in 2025. According to a recent market study on Enterprise Data Transformation by the Intelligent Enterprise ...

Boost your organization's potential with comprehensive data governance, from C-suite support to data quality assurance, retention rules and more. As critical as data is for organizations to flourish ...

Quality data is the cornerstone of good business decisions. To ensure your data is high quality, it must first be measured. Organizations struggle to maintain good data quality, especially as ...