Assuring data quality should be one of the most important goals for IT professionals. This is truer today than it has ever been as organizations rely on data to power their AI and machine learning ...

Data integrity ensures the accuracy and reliability of data across its entire life cycle. Learn more about why data integrity is important.

Collecting and combining diverse data types from different manufacturing processes can play a significant role in improving semiconductor yield, quality, and reliability, but making that happen ...

Inadequate data strategy, poor governance and a lack of collaboration between teams all contribute to companies relying on poor-quality data.

Regardless of which technical path your business pursues, the primary limiting factor you’ll face today is your own data quality.

Training AI models with AI-generated synthetic content causes the quality of the models' outputs to disintegrate, a new paper shows.

Understanding the specific categories of CRM data and how to use them effectively is essential to getting the highest return on your CRM investment.

Microsoft is bringing custom data types to Excel. Businesses and consumers will be able to import structured data into a single cell and reference it throughout a spreadsheet.