Data quality issues emerge from multiple failure points from development practices to production life cycle, each compounding others in ways that are detected only at the end: Improper data testing ...

Chief data officers, VPs of data platforms, and data engineers are dealing with a significant lack of visibility into the complex data stacks they manage, according to a report from data observability ...

As AI moves from hype to measurable results, one truth is becoming clear: Enterprise AI needs business context to be fully trusted.

Big data projects don’t typically fail for a single reason, and certainly not for technology alone. A combination of factors serve to derail big data deployments. Problems and failures occur due to ...

And the reason for this is because there is so much at stake.” Cars and planes need to be extremely reliable because people ...