Feast

Feast is an open-source feature store which whylogs can easily integrate with. Feature stores are used for storing and managing a transformed version of data which is consumable by machine learning models. When monitoring data which feeds a machine learning model, users should monitor both the raw form of the data as well as the transformed version of the data which often lives in a feature store. Data quality issues can be caused by both changes to the raw data and issues which occur during data transformations. By monitoring both raw and transformed data, users can more quickly diagnose the root cause of issues that result in poor model performance.

See this example notebook for help integrating whylogs with a Feast feature store.