AWS has announced the 'next generation' of its SageMaker AI dev platform, including a unified data dashboard.

For instance, customers can integrate Amazon Aurora MySQL, PostgreSQL and other kinds of databases directly with Amazon SageMaker, without needing to build any complex data pipelines first.

AWS expands its widely adopted machine learning service, combining comprehensive data, analytics, and AI capabilities LAS VEGAS--(BUSINESS WIRE)-- At AWS re:Invent, Amazon Web Services, Inc. (AWS ...

Another offering that AWS announced to support the integration is the SageMaker Data Lakehouse, aimed at helping enterprises unify data across Amazon S3 data lakes and Amazon Redshift data warehouses.

SageMaker will get streaming algorithms and better batch processing and pluck data directly from Amazon's S3 storage.

Remote training is exactly the same thing - except the data is transferred from S3 into the standard folder on disk, and the whole workflow executes on SageMaker: ...

SageMaker Unified Studio brings together tools from other AWS services, including the existing SageMaker Studio, to help customers discover, prepare, and process data to build models. "We are seeing a ...

The next generation of SageMaker brings together these capabilities—along with some exciting new features—to give customers all the tools they need for data processing, SQL analytics, ML model ...