Strong data quality checks reduce bias, drift and inconsistencies that can distort analytics and AI outcomes before datasets reach production.

Learn the definition of data quality and discover best practices for maintaining accurate and reliable data. Data quality refers to the reliability, accuracy, consistency, and validity of your data.

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 ...

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In this episode of Need to Know, our series covering the topics and issues influencing markets and the global conversation, Michael Beal, Co-Head of Enterprise Data Science at Bloomberg, discusses the ...

A strong data governance foundation is essential for higher education institutions to deploy trustworthy, effective ...

What will shape enterprise data in 2026? We look at insights from Bloomberg’s Enterprise Data & Tech Summit in London on ...