A Hidden Risk in Snowflake: Why AI-Ready Data Needs Automated CI/CD?
In Snowflake, data failures rarely show up as broken pipelines—they show up as the wrong data after a deploy that looks successful. Increasingly, that same data powers dashboards, operational decisions, and AI models. When the underlying data shifts unexpectedly, the systems built on top of it can make the wrong decisions while everything appears to be working correctly.
Kevin Bair - #TrueDataOps Podcast Ep. 40
Kevin Bair, Vice President of Data Cloud Architecture at Snowflake, is the featured guest on this week's #TrueDataOps podcast. Watch as host Kent Graziano talks with Kevin about how DataOps is more important than ever with the prevalence of AI and discusses the metadata conundrum.
Guy Adams - #TrueDataOps Podcast Ep. 44
Watch this episode of the #TrueDataOps podcast to see Kent talk to DataOps.live's CTO and Co-founder, Guy Adams. Adams forecasts a major shift where business users will independently manage the majority of data products through self-service tools and generative AI.
Bob Muglia - #TrueDataOps Podcast Ep.19 (S2, Ep1)
Foundation models are the idea you can use an immense amount of data to build a model that has fundamental capabilities that can be leveraged in different ways… The idea of AGI is that the intelligence within a model reaches a point where you’d say it has the same level of capability as the average human… I think it will happen within the next 10 years’
