Amazon announced the next generation of Amazon SageMaker, a unified platform for data, analytics, and AI, bringing together widely-adopted AWS machine learning and analytics capabilities. This announcement includes Amazon SageMaker Data and AI Governance, a set of capabilities that streamline the management of data and AI assets. One challenge data teams face is locating, accessing, and collaborating on data and AI models across their organizations. Discovering relevant assets, understanding their context, and obtaining proper access can be time-consuming and complex, potentially hindering productivity and innovation. SageMaker Data and AI Governance offers a comprehensive set of features by providing a unified experience for cataloging, discovering, and governing data and AI assets. It’s centered around SageMaker Catalog built on Amazon DataZone, providing a centralized repository accessible through Amazon SageMaker Unified Studio (preview). The catalog is built directly into the SageMaker platform, offering seamless integration with existing SageMaker workflows and tools, helping engineers, data scientists, and analysts safely find and use authorized data and models through advanced search features. With the SageMaker platform, users can safeguard and protect their AI models using guardrails and implementing responsible AI policies. Some key Data and AI governance features of SageMaker include: Enterprise-ready business catalog, Self-service for data and AI workers, Simplified access to data and tools, Governed data and model sharing, and Bringing a consistent level of AI safety across all your applications. For seamless integration with existing processes, SageMaker Data and AI Governance provides API support, enabling programmatic access for setup and configuration.