A feature store for machine learning is useful for organizations of any size as it allows them to store, manage, and organize their feature data, which is essential for training and deploying machine learning models. This can help organizations improve the quality and performance of their models, streamline the ML development process, and make it easier to collaborate and share data among different teams.
In a large organization, a feature store can help to promote collaboration and sharing of features among teams, which can improve the consistency and standardization of features across different models. This can help to prevent duplication of effort and ensure that all teams are using the same, high-quality features for their models. However, small organizations with limited resources might also benefit from using a feature store as it helps them efficiently manage and use their data.