A feature view is a selection of features (and labels) from one or more feature groups. You create a feature view by joining together features from existing feature groups and optionally performing following steps: defining one or more of the selected features as labels, declaring a transformation (feature encoding) for one or more selected features, and returning only certain feature values by applying a user-supplied filter condition.
As a feature view can include model-dependent transformation functions for features, it can be said to be aware of each feature’s feature type. The feature view also knows about the entity_id (primary key) and event_time columns for each feature in the feature view.
The feature view is a representation of the features (and labels) used by one or more models. As such, it is a model-specific view of features/labels in the feature store. The feature view:
Suppose you have two feature groups for an e-commerce platform: customer_information and purchase_history. You want to create a feature view for predicting customer churn that combines relevant features from both feature groups.