Tuesday, October 15, 11:40am - 12:00pm (EDT)
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24h
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Speaker: Ray Cunningham
The feature store has been the data layer for MLOps platforms that consumed data from both historical data sources (data warehouses, data lakes, etc) and real-time data sources (message buses). Historical data, however, is increasingly found in the Lakehouse - an open transactional data layer (Apache Iceberg, Apache Hudi, Delta) for any query engine. Just as the cloud separated storage and compute, the Lakehouse separates data from query engines. In this talk, we introduce the AI Lakehouse - extensions to the Lakehouse to include MLOps capabilities.
The feature store has been the data layer for MLOps platforms that consumed data from both historical data sources (data warehouses, data lakes, etc) and real-time data sources (message buses). Historical data, however, is increasingly found in the Lakehouse - an open transactional data layer (Apache Iceberg, Apache Hudi, Delta) for any query engine. Just as the cloud separated storage and compute, the Lakehouse separates data from query engines. In this talk, we introduce the AI Lakehouse - extensions to the Lakehouse to include MLOps capabilities.
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Feature Store Summit 2024