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 ...

Technical debt is a well-known concept in software development. It's what happens when unclear or forgotten assumptions are buried inside a complex, interconnected codebase, and it leads to poor ...

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 ...

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 ...

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

As the push to integrate artificial intelligence and increase interoperability evolves, Clinical Architecture sees a dire need for tools that can assess the quality of healthcare data. Poor quality ...

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 ...

The journey from data sharing to improved health outcomes is dependent on high-quality clinical data. Without it, it is difficult for providers to make the best clinical decisions possible, and the ...

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 ...