In some ways, data and its quality can seem strange to people used to assessing the quality of software. There’s often no observable behaviour to check and little in the way of structure to help you ...

Many organizations nowadays are struggling with the quality of their data. Data quality (DQ) problems can arise in various ways. Here are common causes of bad data quality: Multiple data sources: ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

After years of experimentation, AI adoption is at the forefront of enterprise strategies in 2025. According to a recent market study on Enterprise Data Transformation by the Intelligent Enterprise ...

Utilities are becoming increasingly skilled at adapting to changes brought on by the digital age: pressure from automation, disruption from new technology, and challenges with how to ingest, manage, ...

I’m sure that you know an interesting story about dating. Finding that right person is not easy and the journey often ...

Data-driven decisions require data that is trustworthy, available, and timely. Upping the dataops game is a worthwhile way to offer business leaders reliable insights. Measuring quality of any kind ...

We’re just starting to tap the potential of what AI can do. But amid all the breakthroughs, one thing is fundamental: AI is only as good as the data it was trained on. Unlike people, who can draw on ...