Data quality issues emerge from multiple failure points from development practices to production life cycle, each compounding ...

It can be tough to manage data manually, and doing so can sometimes lead to errors or inefficiencies. Spreadsheets can get overly complex, and data quality can suffer. This has become a large enough ...

Forbes contributors publish independent expert analyses and insights. Gary Drenik is a writer covering AI, analytics and innovation. In today’s rapidly transforming world, Data has emerged as a key ...

Data quality in healthcare can directly affect patient outcomes, physicians’ decision-making abilities and more. Unfortunately, there are many examples of data quality issues running rampant in ...

Some 93% of companies believe data is essential to their marketing success, but on average U.S. marketers believe 25% of the data they use to contact customers remains inaccurate. About 91% of ...

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 ...

Cloud service providers have traced the source of silent data errors to defects in CPUs — as many as 1,000 parts per million — which produce faulty results only occasionally and under certain ...

The UK can blame its bad immigration data on Hungary, one of the eight countries which joined the European Union in 2004. Unlike most existing EU countries, the UK government allowed its citizens to ...