Learn the definition of data quality and discover best practices for maintaining accurate and reliable data.

C-level executives should also ensure their AI strategies and business goals are well-aligned. Whether the objective is to ...

Data quality is a complex and context-dependent concept often misunderstood across business, technology, process, and data science domains, with each attributing different issues to it.

Some of the best thinking on new AI-native systems contemplates the quickness of technology generations, and what it means for design.

Poor data quality and integrity compounded with data silos, lack of integration, and a skills gap make the problem more profound.

Key findings show organizations averaging just 42/100 on data trust maturity, with the lowest scores in areas such as remediation workflows, policy enforcement, and reference/master data quality.

Earlier this month, Bloomberg launched its Virtual Data Room (VDR), which is transforming how firms access and evaluate data. Traders Magazine caught up with Brian Doherty, Bloomberg’s Global Head of ...