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Enterprise data infrastructure is simultaneously a call and response to every technological shift — it both enables new products and businesses, while simultaneously evolving to support the demands created by these same innovations. Over the last fifty years, we’ve progressed from traditional on-premise data warehouses to cloud-native data warehouses and data lakes. Today, we’re at an exciting inflection point for the landscape as we’re evolving quickly past the modern data stack due to multiple catalysts that are ushering in a post-modern Data 3.0 era. For one, as we noted last year, AI’s proliferation has led to profound changes within the?AI infrastructure landscape. But in the midst of this major technological shift, another tectonic transformation is afoot. The very core of enterprise data infrastructure is being reimagined due to the impact of a revolutionary architectural paradigm—the data lakehouse—which supports multiple use cases, from analytics to AI workloads, in a powerful, interoperable platform. The lakehouse paradigm doesn’t just represent a marginal improvement to the architectures that came before it. Rather, it is a radical transformation that will bring forth an era of unprecedented interoperability and set the stage for the next wave of multi-billion-dollar data infrastructure giants to emerge. Our full Data 3.0 roadmap here including 4 thesis areas that Lauri J. Moore and I are tracking closely: https://lnkd.in/gAkxqb5b