Amazon SageMaker Feature Store is a new capability of Amazon SageMaker that helps data scientists and machine learning (ML) engineers securely store, discover, and share curated data used in training and prediction workflows. As organizations build data-driven applications using ML, they’re constantly assembling and moving features between more and more functional teams. This constant movement of data can lead to inconsistencies in features and become a bottleneck when designing ML initiatives spanning multiple teams. For example, an ecommerce company might have several data science and engineering teams working on different aspects of their platform. The Core Search team focuses on query understanding and information retrieval tasks. The Product Success team solves problems involving customer reviews and feedback signals. The Personalization team uses clickstream and session data to create ML models for personalized recommendations. Additionally, data engineering teams like the Data Curation team can curate and validate user-specific information, which is

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