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The Data Hub and Spoke: Data Infrastructure “3.0” for the Age of Generative AI - Foundation Capital

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Over the past decade, the term “modern data stack” has come into prominence with the rise of cloud-native software and an increasingly smart, connected world. With workloads shifting to the cloud and an abundance of new, real-time data coming online, enterprises have adopted cloud data warehouses as their systems of record, along with a set of specialized point solutions to aggregate, clean, filter, and analyze this data. This marks an unbundling of the old guard of monolithic, on-prem data infrastructure solutions like Informatica, Teradata, and Alteryx. However, with this explosion in data tooling, we’ve lost some of the benefits of the traditional data stack: most notably, the control, visibility, and ease of use that comes with everything living in a single place. Today’s modern data stack has become overly complex, fragmented, and costly to manage. Moreover, for large enterprises, this stack is difficult to both configure and derive value from on an ongoing basis, as it relies on

Over the past decade, the term “modern data stack” has come into prominence with the rise of cloud-native software and an increasingly smart, connected world. With workloads shifting to the cloud and an abundance of new, real-time data coming online, enterprises have adopted cloud data warehouses as their systems of record, along with a set of specialized point solutions to aggregate, clean, filter, and analyze this data. This marks an unbundling of the old guard of monolithic, on-prem data infrastructure solutions like Informatica, Teradata, and Alteryx. However, with this explosion in…

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