<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Amazon SageMaker Data &amp; AI Governance &#8211; Noise</title>
	<atom:link href="https://noise.getoto.net/tag/amazon-sagemaker-data-ai-governance/feed/" rel="self" type="application/rss+xml" />
	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
	<lastBuildDate>Thu, 20 Nov 2025 18:39:41 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=6.8.2</generator>
	<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>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=79577840ddd0243c772aedef369fcf56</guid>

					<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>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<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>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<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>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<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>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<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>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=6f69e6435589c4a12f65c6c24201ab0b</guid>

					<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>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<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>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<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>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=61342f42bd9c129f91bda70c8e0c07aa</guid>

					<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>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<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>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Automate data lineage in Amazon SageMaker using AWS Glue Crawlers supported data sources</title>
		<link>https://noise.getoto.net/2025/07/30/automate-data-lineage-in-amazon-sagemaker-using-aws-glue-crawlers-supported-data-sources/</link>
		
		<dc:creator><![CDATA[Mohit Dawar]]></dc:creator>
		<pubDate>Wed, 30 Jul 2025 16:33:20 +0000</pubDate>
				<category><![CDATA[Amazon DataZone]]></category>
		<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[AWS Glue]]></category>
		<category><![CDATA[AWS Glue Crawlers]]></category>
		<category><![CDATA[Data Lineage]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=d9247d9b3d882026ef53623cccb4358c</guid>

					<description><![CDATA[In this post, we explore its real-world impact through the lens of an ecommerce company striving to boost their bottom line. To illustrate this practical application, we walk you through how you can use the prebuilt integration between SageMaker Catalog and AWS Glue crawlers to automatically capture lineage for data assets stored in Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>AWS Weekly Roundup: SQS fair queues, CloudWatch generative AI observability, and more (July 28, 2025)</title>
		<link>https://noise.getoto.net/2025/07/28/aws-weekly-roundup-sqs-fair-queues-cloudwatch-generative-ai-observability-and-more-july-28-2025/</link>
		
		<dc:creator><![CDATA[Micah Walter]]></dc:creator>
		<pubDate>Mon, 28 Jul 2025 16:56:04 +0000</pubDate>
				<category><![CDATA[Amazon CloudWatch]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon Simple Queue Service (SQS)]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Identity and Access Management (IAM)]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<category><![CDATA[Week in Review]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=8689aec65f87ca0078b61c97986dec77</guid>

					<description><![CDATA[To be honest, I’m still recovering from the AWS Summit in New York, doing my best to level up on launches like Amazon Bedrock AgentCore (Preview) and Amazon Simple Storage Service (S3) Vectors. There’s a lot of new stuff to learn! Meanwhile, it’s been an exciting week for AWS builders focused on reliability and observability. […]]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Introducing MCP Server for Apache Spark History Server for AI-powered debugging and optimization</title>
		<link>https://noise.getoto.net/2025/07/23/introducing-mcp-server-for-apache-spark-history-server-for-ai-powered-debugging-and-optimization/</link>
		
		<dc:creator><![CDATA[Manabu McCloskey]]></dc:creator>
		<pubDate>Wed, 23 Jul 2025 18:52:37 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[announcements]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=e2e8b529fb31e247af0ff6e1ffa69849</guid>

					<description><![CDATA[Today, we're announcing the open source release of Spark History Server MCP, a specialized Model Context Protocol (MCP) server that transforms this workflow by enabling AI assistants to access and analyze your existing Spark History Server data through natural language interactions. This project, developed collaboratively by AWS open source and Amazon SageMaker Data Processing, turns complex debugging sessions into conversational interactions that deliver faster, more accurate insights without requiring changes to your current Spark infrastructure. You can use this MCP server with your self-managed or AWS managed Spark History Servers to analyze Spark applications running in the cloud or on-premises deployments.]]></description>
		
		
		<enclosure url="https://d2908q01vomqb2.cloudfront.net/artifacts/DBSBlogs/BDB-5378/shs_mcp_glue_and_emr_ec2_demo2.mP4" length="157898542" type="video/mp4" />

			</item>
		<item>
		<title>Unifying data insights with Amazon QuickSight and Amazon SageMaker</title>
		<link>https://noise.getoto.net/2025/07/18/unifying-data-insights-with-amazon-quicksight-and-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Ramon Lopez]]></dc:creator>
		<pubDate>Fri, 18 Jul 2025 20:26:38 +0000</pubDate>
				<category><![CDATA[Amazon QuickSight]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[launch]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=d884cde82a670d59027e41f093be70df</guid>

					<description><![CDATA[Amazon SageMaker has announced an integration with Amazon QuickSight, bringing together data in SageMaker seamlessly with QuickSight capabilities like interactive dashboards, pixel perfect reports and generative business intelligence (BI)—all in a governed and automated manner. In this post, we walk through the complete process of integrating Amazon QuickSight with Amazon SageMaker Unified Studio, demonstrating how teams can move from raw data to published dashboards in a secure and governed environment.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Unifying metadata governance across Amazon SageMaker and Collibra</title>
		<link>https://noise.getoto.net/2025/07/16/unifying-metadata-governance-across-amazon-sagemaker-and-collibra/</link>
		
		<dc:creator><![CDATA[Vasiliki Nikolopoulou]]></dc:creator>
		<pubDate>Wed, 16 Jul 2025 18:33:27 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[generative AI]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=13018f987542255c6d1e263ac574acde</guid>

					<description><![CDATA[Amazon Web Services (AWS) and Collibra have built a new integrated solution that demonstrates the integration between the Collibra Platform and the next generation of Amazon SageMaker. In this post, we take a closer look at the integration, describe the use cases it enables, walk through the architecture, and show how to implement the solution in your environment.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Develop and monitor a Spark application using existing data in Amazon S3 with Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/07/09/develop-and-monitor-a-spark-application-using-existing-data-in-amazon-s3-with-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Amit Maindola]]></dc:creator>
		<pubDate>Wed, 09 Jul 2025 19:31:24 +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[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=cf4b208134e6c7fb239b6312a43259f8</guid>

					<description><![CDATA[In this post, we demonstrate how to develop and monitor a Spark application using existing data in Amazon S3 using SageMaker Unified Studio. The solution addresses key challenges organizations face in managing big data analytics workloads through an integrated development environment where data teams can develop, test, and refine Spark applications while leveraging EMR Serverless for dynamic resource allocation and built-in monitoring tools.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Embracing event driven architecture to enhance resilience of data solutions built on Amazon SageMaker</title>
		<link>https://noise.getoto.net/2025/06/05/embracing-event-driven-architecture-to-enhance-resilience-of-data-solutions-built-on-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Dhrubajyoti Mukherjee]]></dc:creator>
		<pubDate>Thu, 05 Jun 2025 16:43:50 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Well-Architected]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=4e5fe02518ae3127a9ef0adfe366cb59</guid>

					<description><![CDATA[This post provides guidance on how you can use event driven architecture to enhance the resiliency of data solutions built on the next generation of Amazon SageMaker, a unified platform for data, analytics, and AI. SageMaker is a managed service with high availability and durability.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Connect, share, and query where your data sits using Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/03/21/connect-share-and-query-where-your-data-sits-using-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Lakshmi Nair]]></dc:creator>
		<pubDate>Fri, 21 Mar 2025 14:34:12 +0000</pubDate>
				<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[Analytics]]></category>
		<category><![CDATA[data governance]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=e3c81bbfcf8c5de0cf2605315a21104f</guid>

					<description><![CDATA[In this blog post, we will demonstrate how business units can use Amazon SageMaker Unified Studio to discover, subscribe to, and analyze these distributed data assets. Through this unified query capability, you can create comprehensive insights into customer transaction patterns and purchase behavior for active products without the traditional barriers of data silos or the need to copy data between systems.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
	</channel>
</rss>

<!--
Performance optimized by W3 Total Cache. Learn more: https://www.boldgrid.com/w3-total-cache/

Object Caching 70/290 objects using Memcached
Page Caching using Disk: Enhanced 
Lazy Loading (feed)
Database Caching using Memcached

Served from: noise.getoto.net @ 2025-12-07 18:31:07 by W3 Total Cache
-->