Category: HAQM SageMaker Lakehouse

HAQM SageMaker Lakehouse is a unified, open, and secure data lakehouse that now seamlessly integrates with HAQM S3 Tables, the first cloud object store with built-in Apache Iceberg support. In this post, we guide you how to use various analytics services using the integration of SageMaker Lakehouse with S3 Tables.

HAQM SageMaker Catalog now supports metadata rules allowing organizations to enforce metadata standards across data publishing and subscription workflows. In this post, we guide you through two workflows: setting up metadata enforcement rules for a specific domain and publishing an asset or data product in a catalog, and setting up metadata enforcement rules for a specific domain and subscribing to an asset or data product that is owned by a project within that domain.

In this post, we demonstrate how to get started with S3 Tables and HAQM Redshift Serverless for querying data in Iceberg tables. We show how to set up S3 Tables, load data, register them in the unified data lake catalog, set up basic access controls in SageMaker Lakehouse through AWS Lake Formation, and query the data using HAQM Redshift.

In this blog post, we will demonstrate how business units can use HAQM SageMaker Unified Studio to discover, subscribe to, and analyze these distributed data assets. Through this unified query capability, you can create comprehensive insights into customer transaction patterns and purchase behavior for active products without the traditional barriers of data silos or the need to copy data between systems.