Feature Store Usage Patterns - From a Single Data Scientist to an Enterprise

Feature stores increase productivity for ML data scientists, from a single-person team to a large, globally distributed enterprise. Over the last few years, we’ve observed these different modes of adoption with feature stores. The ways small teams and big enterprises use them vary vastly. But there is a unifying thread between all stages of adoption. The ability to build upon the underlying abstractions provided allows feature storesto organically scale to any size. In this presentation, I'll share our learnings from different companies on usage patterns of feature stores.