What is a Feature Store? - Tecton

Data teams are starting to realize that operational machine learning requires solving data problems that extend far beyond the creation of data pipelines. In Tecton's previous post, Why We Need DevOps for ML Data, we highlighted some of the key data challenges that teams face when productionizing ML systems. However, operational machine learning -- ML-driven intelligence built into customer-facing applications -- is new for most teams. A new kind of ML-specific data infrastructure is emerging to make that possible. Increasingly Data Science and Data Engineering teams are turning towards feature stores to manage the data sets and data pipelines needed to productionize their ML applications.