Feature store

A feature store is a centralized repository used in machine learning to store, manage, and serve features for model training and inference.^[1] It provides a unified interface for data scientists and engineers to access curated, reusable features derived from raw data, ensuring consistency between training and production environments.^[2] Feature stores typically support batch and real-time data pipelines, enabling efficient feature computation, storage, and retrieval at scale.

Feature stores play a critical role in operationalizing machine learning systems by improving reproducibility, reducing data leakage, and promoting collaboration across teams.^[3] They often have features like feature versioning, metadata management, and access control that help keep data quality and governance high.^[4]

See also

• Machine learning
• Feature engineering
• Data pipeline
• Data warehouse
• Data lake
• MLOps
• Data preprocessing
• Big data

References

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