Amazon SageMaker Catalog
Discover, govern, and collaborate on data and AI securely
Overview
The next generation of Amazon SageMaker simplifies the discovery, governance, and collaboration for data and AI across your structured and unstructured data, AI models, business intelligence dashboards, and applications. With Amazon SageMaker Catalog, you can securely discover and access approved data and models using semantic search with generative AI–created metadata or just ask Amazon Q Developer with natural language to find your data. Users can consistently define and enforce access policies using a single permission model with fine-grained access controls centrally in the Amazon SageMaker Unified Studio. Seamlessly share and collaborate on data and AI assets through easy publishing and subscribing workflows. Build trust throughout your organization with data quality monitoring, data classification, and data and machine learning (ML) lineage.
See Amazon SageMaker Catalog in action

Benefits
Features
Customers
Natera, Inc.
“By integrating Amazon QuickSight with Amazon SageMaker, our lab operations teams and scientists can now monitor clinical test performance across all sites in real time. We’ve developed unified dashboards that consolidate throughput, quality control metrics, and turnaround times, enabling detailed trend analysis and ongoing performance optimization. Scientists can now perform comprehensive data analysis – from exploratory review to model development – all within a single, integrated environment.”
Mirko Buholzer, VP of Software Engineering, Natera, Inc.
Cisco
"You want to discover, share, and govern your data. Whether you call it a data mesh or a data fabric, data exists across different teams in multiple silos, and you need a way to bring it together. Amazon SageMaker Catalog connects data producers and consumers, enabling producers to share data with built-in controls and data contracts while allowing consumers to access the data using the tools of their choice"
Shaja Arul Selvamani, Sr. Director AI/ML, Cisco

NatWest
"Our Data Platform Engineering team has been deploying multiple end-user tools for data engineering, ML, SQL, and gen AI tasks. As we look to simplify processes across the bank, we’ve been looking at streamlining user authentication and data access authorization. Amazon SageMaker delivers a ready-made user experience to help us deploy one single environment across the organization, reducing the time required for our data users to access new tools by around 50%."
Zachery Anderson, CDAO, NatWest Group

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