โ๏ธAWS Machine Learning BlogโขStalecollected in 10m
New capabilities in Amazon SageMaker Feature Store
#mlops#data-engineering#feature-storeamazon-sagemaker-feature-storeamazon-sagemakeraws-lake-formationapache-iceberg
๐กBoost your ML pipeline efficiency with new governance and storage features in SageMaker Feature Store.
โก 30-Second TL;DR
What Changed
Enhanced governance with Lake Formation integration
Why It Matters
Reduces operational overhead for ML engineers by simplifying data governance and improving the performance of feature retrieval.
What To Do Next
Upgrade to SageMaker Python SDK v3.8.0 and test the new Iceberg table integration for your feature pipelines.
Who should care:Developers & AI Engineers
Key Points
- โขEnhanced governance with Lake Formation integration
- โขImproved data management via Iceberg table properties
- โขStreamlined ML feature pipeline development in SDK v3.8.0
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Original source: AWS Machine Learning Blog โ