Category: Analytics

Amazon S3 Tables integration with SageMaker Lakehouse enables unified access to S3 Tables data from AWS analytics engines like Amazon Athena, Redshift, EMR, and third-party query engines, to build securely and manage centrally.

Find solutions to your most critical business challenges with ease. Amazon Q in QuickSight enables business users to perform complex scenario analysis up to 10x faster than spreadsheets.

Connect, discover, and govern data across silos with Amazon SageMaker Lakehouse’s new data catalog and permissions capabilities, enabling centralized access and fine-grained controls.

Simplify data replication and ingestion from applications such as Salesforce, SAP, ServiceNow, and Zendesk, to Amazon SageMaker Lakehouse and Amazon Redshift.

Unifying data silos, Amazon SageMaker Lakehouse seamlessly integrates S3 data lakes and Redshift warehouses, enabling unified analytics and AI/ML on a single data copy through open Apache Iceberg APIs and fine-grained access controls.

Effortlessly analyze operational data in Amazon SageMaker Lakehouse, freeing developers from building custom pipelines and enabling seamless insights extraction.

Manage data and AI assets through a unified catalog, granular access controls, and a consistent policy enforcement. Establish trust via automation – boost productivity and innovation for data teams.

Realize visual traceability of data origins, transformations, and usage – bolstering trust, governance, and discoverability for strategic data-driven decisions.