Build an offline feature store using Amazon SageMaker Unified Studio and SageMaker Catalog
📰 AWS Machine Learning
Build an offline feature store using Amazon SageMaker Unified Studio and SageMaker Catalog
Action Steps
- Set up a SageMaker Unified Studio domain
- Create a SageMaker Catalog
- Implement a publish-subscribe pattern for data producers and consumers
- Configure data producers to publish curated feature tables
- Configure data consumers to discover, subscribe to, and reuse feature tables
Who Needs to Know This
Data scientists and engineers on a team can benefit from this solution as it enables them to securely discover, subscribe to, and reuse curated feature tables for model development. This improves collaboration and reduces data duplication
Key Insight
💡 Using a publish-subscribe pattern enables secure discovery, subscription, and reuse of curated feature tables
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📈 Build an offline feature store with SageMaker Unified Studio and SageMaker Catalog
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