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	<title>Amazon SageMaker Data &amp; AI Governance &#8211; Noise</title>
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		<title>Build governance dashboards for Amazon SageMaker Catalog with Amazon Quick</title>
		<link>https://noise.getoto.net/2026/06/04/build-governance-dashboards-for-amazon-sagemaker-catalog-with-amazon-quick/</link>
		
		<dc:creator><![CDATA[Steve Phillips]]></dc:creator>
		<pubDate>Thu, 04 Jun 2026 15:41:17 +0000</pubDate>
				<category><![CDATA[Amazon Quick Suite]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In a previous post, we showed you how to query Amazon SageMaker Catalog metadata using SQL by using the metadata export feature. This post builds on that foundation by demonstrating how to create governance dashboards with Amazon Quick.]]></description>
		
		
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			</item>
		<item>
		<title>Accelerate SQL development with SageMaker Data Agent in Query Editor</title>
		<link>https://noise.getoto.net/2026/06/04/accelerate-sql-development-with-sagemaker-data-agent-in-query-editor/</link>
		
		<dc:creator><![CDATA[Jason Ramos]]></dc:creator>
		<pubDate>Thu, 04 Jun 2026 15:40:11 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, you learn how to use Data Agent in Query Editor to explore data, build multi-step analyses, recover from errors, and summarize results using a public education dataset.]]></description>
		
		
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			</item>
		<item>
		<title>How Amazon is moving to integrate catalogs to improve data discovery with Amazon SageMaker</title>
		<link>https://noise.getoto.net/2026/05/22/how-amazon-is-moving-to-integrate-catalogs-to-improve-data-discovery-with-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Pradeep Misra]]></dc:creator>
		<pubDate>Fri, 22 May 2026 20:56:25 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Enterprises face challenges when teams create data assets outside of central data catalogs. It adds overhead for discovery, and limits collaboration. Amazon’s Business Data Technologies (BDT) team has built an enterprise data catalog Andes for sharing datasets under well-defined policies. However, teams created catalog of local datasets and other non-tabular assets such as dashboards and metrics, outside Andes. This made it difficult to discover all assets in a consolidated way. In this post, we share how Amazon.com is working to integrate catalogs by extending enterprise data catalog Andes with Amazon SageMaker.]]></description>
		
		
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		<item>
		<title>Analyzing your data catalog: Query SageMaker Catalog metadata with SQL</title>
		<link>https://noise.getoto.net/2026/04/22/analyzing-your-data-catalog-query-sagemaker-catalog-metadata-with-sql/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Wed, 22 Apr 2026 15:37:38 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we demonstrate how to use the metadata export capability in Amazon SageMaker Catalog and perform analytics such as historical changes, monitor asset growth and track metadata improvements.]]></description>
		
		
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			</item>
		<item>
		<title>Navigating multi-account deployments in Amazon SageMaker Unified Studio: a governance-first approach</title>
		<link>https://noise.getoto.net/2026/04/01/navigating-multi-account-deployments-in-amazon-sagemaker-unified-studio-a-governance-first-approach/</link>
		
		<dc:creator><![CDATA[Ben Shafabakhsh]]></dc:creator>
		<pubDate>Wed, 01 Apr 2026 19:12:46 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we explore SageMaker Unified Studio multi-account deployments in depth: what they entail, why they matter, and how to implement them effectively. We examine architecture patterns, evaluate trade-offs across security boundaries, operational overhead, and team autonomy. We also provide practical guidance to help you design a deployment that balances centralized control with distributed ownership across your organization.]]></description>
		
		
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		<item>
		<title>Automating data classification in Amazon SageMaker Catalog using an AI agent</title>
		<link>https://noise.getoto.net/2026/03/24/automating-data-classification-in-amazon-sagemaker-catalog-using-an-ai-agent/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Tue, 24 Mar 2026 21:44:32 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[If you’re struggling with manual data classification in your organization, the new Amazon SageMaker Catalog AI agent can automate this process for you. Most large organizations face challenges with the manual tagging of data assets, which doesn’t scale and is unreliable. In some cases, business terms aren’t applied consistently across teams. Different groups name and tag data assets based on local conventions. This creates a fragmented catalog where discovery becomes unreliable and governance teams spend more time normalizing metadata than governing. In this post, we show you how to implement this automated classification to help reduce the manual tagging effort and improve metadata consistency across your organization.]]></description>
		
		
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			</item>
		<item>
		<title>Implement a data mesh pattern in Amazon SageMaker Catalog without changing applications</title>
		<link>https://noise.getoto.net/2026/02/23/implement-a-data-mesh-pattern-in-amazon-sagemaker-catalog-without-changing-applications/</link>
		
		<dc:creator><![CDATA[Paolo Romagnoli]]></dc:creator>
		<pubDate>Mon, 23 Feb 2026 19:41:32 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=abce3ff4bd8cd4330f0e1d4cb90e28a1</guid>

					<description><![CDATA[In this post, we walk through simulating a scenario based on data producer and data consumer that exists before Amazon SageMaker Catalog adoption. We use a sample dataset to simulate existing data and an existing application using an AWS Lambda function, then implement a data mesh pattern using Amazon SageMaker Catalog while keeping your current data repositories and consumer applications unchanged.]]></description>
		
		
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			</item>
		<item>
		<title>Build a trusted foundation for data and AI using Alation and Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2026/01/30/build-a-trusted-foundation-for-data-and-ai-using-alation-and-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Anthony Lempelius, James Mesney]]></dc:creator>
		<pubDate>Thu, 29 Jan 2026 23:33:30 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[The Alation and SageMaker Unified Studio integration helps organizations bridge the gap between fast analytics and ML development and the governance requirements most enterprises face. By cataloging metadata from SageMaker Unified Studio in Alation, you gain a governed, discoverable view of how assets are created and used. In this post, we demonstrate who benefits from this integration, how it works, the specific metadata it synchronizes, and provide a complete deployment guide for your environment.]]></description>
		
		
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			</item>
		<item>
		<title>Navigating architectural choices for a lakehouse using Amazon SageMaker</title>
		<link>https://noise.getoto.net/2026/01/12/navigating-architectural-choices-for-a-lakehouse-using-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Lakshmi Nair]]></dc:creator>
		<pubDate>Mon, 12 Jan 2026 20:46:27 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
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					<description><![CDATA[Over time, several distinct lakehouse approaches have emerged. In this post, we show you how to evaluate and choose the right lakehouse pattern for your needs. A lakehouse architecture isn’t about choosing between a data lake and a data warehouse. Instead, it’s an approach to interoperability where both frameworks coexist and serve different purposes within a unified data architecture. By understanding fundamental storage patterns, implementing effective catalog strategies, and using native storage capabilities, you can build scalable, high-performance data architectures that support both your current analytics needs and future innovation.]]></description>
		
		
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		<item>
		<title>AWS analytics at re:Invent 2025: Unifying Data, AI, and governance at scale</title>
		<link>https://noise.getoto.net/2026/01/08/aws-analytics-at-reinvent-2025-unifying-data-ai-and-governance-at-scale/</link>
		
		<dc:creator><![CDATA[Larry Weber]]></dc:creator>
		<pubDate>Wed, 07 Jan 2026 22:44:25 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Managed Workflows for Apache Airflow (Amazon MWAA)]]></category>
		<category><![CDATA[Amazon OpenSearch Service]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=ff20917a3d0a5ec52a0043e684e9594d</guid>

					<description><![CDATA[re:Invent 2025 showcased the bold Amazon Web Services (AWS) vision for the future of analytics, one where data warehouses, data lakes, and AI development converge into a seamless, open, intelligent platform, with Apache Iceberg compatibility at its core. Across over 18 major announcements spanning three weeks, AWS demonstrated how organizations can break down data silos, […]]]></description>
		
		
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		<item>
		<title>Reference guide for building a self-service analytics solution with Amazon SageMaker</title>
		<link>https://noise.getoto.net/2025/12/16/reference-guide-for-building-a-self-service-analytics-solution-with-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Tue, 16 Dec 2025 21:47:23 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we show how to use Amazon SageMaker Catalog to publish data from multiple sources, including Amazon S3, Amazon Redshift, and Snowflake. This approach enables self-service access while ensuring robust data governance and metadata management.]]></description>
		
		
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			</item>
		<item>
		<title>How Bayer transforms Pharma R&#038;D with a cloud-based data science ecosystem using Amazon SageMaker</title>
		<link>https://noise.getoto.net/2025/12/13/how-bayer-transforms-pharma-rd-with-a-cloud-based-data-science-ecosystem-using-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Avinash Erupaka]]></dc:creator>
		<pubDate>Fri, 12 Dec 2025 23:06:25 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=c8382077f4eb387fd65fc8dd3f359cd9</guid>

					<description><![CDATA[In this post, we discuss how Bayer AG used the next generation of Amazon SageMaker to build a cloud-based Pharma R&#38;D Data Science Ecosystem (DSE) that unified data ingestion, storage, analytics, and AI/ML workflows.]]></description>
		
		
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		<item>
		<title>Enforce business glossary classification rules in Amazon SageMaker Catalog</title>
		<link>https://noise.getoto.net/2025/11/20/enforce-business-glossary-classification-rules-in-amazon-sagemaker-catalog/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Thu, 20 Nov 2025 18:39:41 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Amazon SageMaker Catalog now supports metadata enforcement rules for glossary terms classification (tagging) at the asset level. With this capability, administrators can require that assets include specific business terms or classifications. Data producers must apply required glossary terms or classifications before an asset can be published. In this post, we show how to enforce business glossary classification rules in SageMaker Catalog.]]></description>
		
		
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		<item>
		<title>Enhanced data discovery in Amazon SageMaker Catalog with custom metadata forms and rich text documentation</title>
		<link>https://noise.getoto.net/2025/11/20/enhanced-data-discovery-in-amazon-sagemaker-catalog-with-custom-metadata-forms-and-rich-text-documentation/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Thu, 20 Nov 2025 18:35:07 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[announcements]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=c5aad1c5162dc0a43d822c03a03ed42e</guid>

					<description><![CDATA[Amazon SageMaker Catalog now supports custom metadata forms and rich text descriptions at the column level, extending existing curation capabilities for business names, descriptions, and glossary term classifications. Column-level context is essential for understanding and trusting data. This release helps organizations improve data discoverability, collaboration, and governance by letting metadata stewards document columns using structured and formatted information that aligns with internal standards. In this post, we show how to enhance data discovery in SageMaker Catalog with custom metadata forms and rich text documentation at the schema level.]]></description>
		
		
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		<item>
		<title>Cross-account lakehouse governance with Amazon S3 Tables and SageMaker Catalog</title>
		<link>https://noise.getoto.net/2025/11/19/cross-account-lakehouse-governance-with-amazon-s3-tables-and-sagemaker-catalog/</link>
		
		<dc:creator><![CDATA[Sneha Rao]]></dc:creator>
		<pubDate>Tue, 18 Nov 2025 23:01:03 +0000</pubDate>
				<category><![CDATA[Amazon S3 Tables]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=db33ca2fd4775222f9738327601c9b25</guid>

					<description><![CDATA[In this post, we walk you through a practical solution for secure, efficient cross-account data sharing and analysis. You’ll learn how to set up cross-account access to S3 Tables using federated catalogs in Amazon SageMaker, perform unified queries across accounts with Amazon Athena in Amazon SageMaker Unified Studio, and implement fine-grained access controls at the column level using AWS Lake Formation.]]></description>
		
		
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		<item>
		<title>Accelerate data governance with custom subscription workflows in Amazon SageMaker</title>
		<link>https://noise.getoto.net/2025/10/24/accelerate-data-governance-with-custom-subscription-workflows-in-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Nira Jaiswal]]></dc:creator>
		<pubDate>Fri, 24 Oct 2025 20:41:19 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=fc436357edd70bdb9d7ab4bbb4782a85</guid>

					<description><![CDATA[Organizations need to efficiently manage data assets while maintaining governance controls in their data marketplaces. Although manual approval workflows remain important for sensitive datasets and production systems, there’s an increasing need for automated approval processes with less sensitive datasets. In this post, we show you how to automate subscription request approvals within SageMaker, accelerating data access for data consumers.]]></description>
		
		
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		<title>Automate email notifications for governance teams working with Amazon SageMaker Catalog</title>
		<link>https://noise.getoto.net/2025/10/21/automate-email-notifications-for-governance-teams-working-with-amazon-sagemaker-catalog/</link>
		
		<dc:creator><![CDATA[Himanshu Sahni]]></dc:creator>
		<pubDate>Tue, 21 Oct 2025 20:59:53 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we show you how to create custom notifications for events occurring in SageMaker Catalog using Amazon EventBridge, AWS Lambda, and Amazon SNS. You can expand this solution to automatically integrate SageMaker Catalog with in-house enterprise workflow tools like ServiceNow and Helix.]]></description>
		
		
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		<item>
		<title>Visualize data lineage using Amazon SageMaker Catalog for Amazon EMR, AWS Glue, and Amazon Redshift</title>
		<link>https://noise.getoto.net/2025/10/13/visualize-data-lineage-using-amazon-sagemaker-catalog-for-amazon-emr-aws-glue-and-amazon-redshift/</link>
		
		<dc:creator><![CDATA[Shubham Purwar]]></dc:creator>
		<pubDate>Mon, 13 Oct 2025 19:08:49 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=89e754efcbf447ec16867fdb98ac995b</guid>

					<description><![CDATA[Amazon SageMaker offers a comprehensive hub that integrates data, analytics, and AI capabilities, providing a unified experience for users to access and work with their data. Through Amazon SageMaker Unified Studio, a single and unified environment, you can use a wide range of tools and features to support your data and AI development needs, including […]]]></description>
		
		
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		<title>Introducing restricted classification terms for governed classification in Amazon SageMaker Catalog</title>
		<link>https://noise.getoto.net/2025/09/08/introducing-restricted-classification-terms-for-governed-classification-in-amazon-sagemaker-catalog/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Mon, 08 Sep 2025 20:36:39 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Security and compliance concerns are key considerations when customers across industries rely on Amazon SageMaker Catalog. Customers use SageMaker Catalog to organize, discover, and govern data and machine learning (ML) assets. A common request from domain administrators is the ability to enforce governance controls on certain metadata terms that carry compliance or policy significance. Examples […]]]></description>
		
		
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		<title>Develop and deploy a generative AI application using Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/08/04/develop-and-deploy-a-generative-ai-application-using-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Amit Maindola]]></dc:creator>
		<pubDate>Mon, 04 Aug 2025 17:17:02 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Financial Services]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=d47a545af39189a411ec5c80ca2c10fb</guid>

					<description><![CDATA[In this post, we demonstrate how to use Amazon Bedrock Flows in SageMaker Unified Studio to build a sophisticated generative AI application for financial analysis and investment decision-making.]]></description>
		
		
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