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

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 ...

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 ...

The Office for National Statistics (ONS) has published guidelines to improve the quality of data in the public sector. The Government data quality framework, developed by the Government Data Quality ...

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 ...

Many organizations invest heavily in tracking and improving the customer journey to support customer satisfaction (CSAT) and Net Promoter Scores (NPS), but they still struggle to make a measurable ...

Through literature review and collaborative design, we propose the Focus, Activity, Statistic, Scale type, and Reference (FASStR) framework to provide a systematic approach to health care operation ...

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 ...

Did you know your company’s data privacy practices can be a competitive differentiator? Usually, we think of competitive differentiators around the level of service you provide, the quality of your ...

Forbes contributors publish independent expert analyses and insights. The path to enterprise AI maturity runs directly through data. However, constructing AI-ready data platforms is more than just a ...