An Azure Machine Learning managed feature store lets you discover, create, and operationalize features. Features serve as the connective tissue in the machine learning lifecycle, starting from the prototyping phase, where you experiment with various features. That lifecycle continues to the operationalization phase, where you deploy your models, and inference steps look up the feature data. For more information about feature stores, read the [feature store concepts](./concept-what-is-managed-feature-store.md) document.
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