Everyone wants successful AI, but the reality is that this demands trusted data products at unprecedented speed. However, fragmented tools and siloed approaches are slowing enterprise progress.
DBTA recently held a roundtable webinar, Speed + Trust: The Winning Formula for AI-Ready Data Products, with experts who explored how leaders in the market are solving the fundamental challenges that come with creating trusted, reusable data products to enable confident AI deployment at scale.
“The last couple of years we’ve had this honeymoon phase with AI,” said John O’brien, principal advisor and industry analyst as Radiant Advisors. “Don’t get discouraged, there are challenges with new technologies.”
One of the biggest challenges is AI is “confidently wrong” and that drives down ROI, said Yetkin Ozkucur, global sales engineering director at Quest.
“Our clients need to keep pace with AI, they need to get their hands on the data, and they need to get their hands on data quickly,” said Susan Laine, chief technologist at Quest.
A trusted data product can change what’s possible with AI, O’Brien said. A fragmented approach is too difficult to maintain. Managing data as a product transforms raw data into a strategic, business-aligned resource. The platform needs to be trustworthy, reusable, discoverable, accessible, and composable.
Laine described how Quest's unified erwin Data Management Platform eliminates data silos through AI-enabled data automation, delivering trusted data products up to 54% faster than traditional approaches.
“All these disciplines are coming together to solve these use cases,” Laine said. “The Autonomous Data Product is turning heads…because it’s finally interweaving in all these great disciplines.”
Once we’re in a new AI era with autonomous agents and projects, the evolution toward converged data management platforms will be realized without vendor lock-in, Ozkucur said.
For the full webinar, featuring a more in-depth discussion, Q&A, and more, you can view an archived version of the webinar here.