Data quality and the metrics used to measure performance are among the biggest challenges facing the pensions industry as it moves towards a new value for money framework designed to make it easier ...

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 ...

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 ...

This integrated model delineates the multi-stakeholder architecture essential for medical data assetization and governance. The ecosystem is centered on a trusted data space platform that facilitates ...

In this podcast, we talk with Cody David, solutions architect with Syniti, which is part of Capgemini, about the importance of ensuring data quality for artificial intelligence (AI) workloads. Being ...

A new framework developed by researchers at Google Cloud and DeepMind aims to address one of the key challenges of developing computer use agents (CUAs): Gathering high-quality training examples at ...