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	<title>Amazon SageMaker Unified Studio &#8211; Noise</title>
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	<lastBuildDate>Mon, 28 Sep 2026 15:45:42 +0000</lastBuildDate>
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		<title>Enforce IAM permissions boundaries for Amazon SageMaker Unified Studio Tooling blueprints</title>
		<link>https://noise.getoto.net/2026/09/28/enforce-iam-permissions-boundaries-for-amazon-sagemaker-unified-studio-tooling-blueprints/</link>
		
		<dc:creator><![CDATA[Sanjana Sekar]]></dc:creator>
		<pubDate>Mon, 28 Sep 2026 15:45:42 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[AWS Identity and Access Management (IAM)]]></category>
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					<description><![CDATA[Amazon SageMaker Unified Studio now supports custom permissions boundaries for the IAM roles its Tooling blueprint creates. Learn how to create a permissions boundary that restricts AI agent capabilities, configure it on the Tooling blueprint with the AWS CLI, and validate that every provisioned role carries the boundary.]]></description>
		
		
		
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		<item>
		<title>Configure domain-level VPC networking in Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2026/09/23/configure-domain-level-vpc-networking-in-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Prasad Nadig]]></dc:creator>
		<pubDate>Wed, 23 Sep 2026 18:36:56 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Amazon VPC]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Configuring VPC networking per project across a SageMaker Unified Studio domain creates inconsistent, hard-to-audit networks. This post shows administrators how to configure domain-level VPC networking once, so every new project automatically inherits consistent, private network isolation, then update existing projects and validate connectivity.]]></description>
		
		
		
			</item>
		<item>
		<title>Query unstructured data in Amazon SageMaker Catalog using generative AI</title>
		<link>https://noise.getoto.net/2026/09/23/query-unstructured-data-in-amazon-sagemaker-catalog-using-generative-ai/</link>
		
		<dc:creator><![CDATA[Nishchai JM]]></dc:creator>
		<pubDate>Wed, 23 Sep 2026 18:22:00 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In Part 2 of this series, sign in as a data consumer, subscribe to enriched unstructured data assets in Amazon SageMaker Catalog, and query them using natural language through a no-code Amazon Bedrock chat agent and Amazon Bedrock model inference.]]></description>
		
		
		
			</item>
		<item>
		<title>Discover and govern Snowflake data using SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2026/09/16/discover-and-govern-snowflake-data-using-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Marco Duarte]]></dc:creator>
		<pubDate>Wed, 16 Sep 2026 15:19:51 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Connect Snowflake to Amazon SageMaker Unified Studio to build a unified data catalog. Query federated Snowflake tables without moving data, publish enriched assets to SageMaker Catalog, and validate data quality with AWS Glue Data Quality, all while keeping data in Snowflake.]]></description>
		
		
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		<item>
		<title>Connect Amazon SageMaker Unified Studio to Microsoft Power BI – Part 1: IAM Identity Center (IDC)-based domains</title>
		<link>https://noise.getoto.net/2026/09/15/connect-amazon-sagemaker-unified-studio-to-microsoft-power-bi-part-1-iam-identity-center-idc-based-domains/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Tue, 15 Sep 2026 20:55:26 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Connect Microsoft Power BI directly to governed data in Amazon SageMaker Unified Studio using new authentication modes in the Amazon Athena ODBC driver, with no third-party ODBC-JDBC bridge. Part 1 covers IAM Identity Center (IDC)-based domains with both DSN-based and DSN-less connection methods.]]></description>
		
		
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		<item>
		<title>Connect Amazon SageMaker Unified Studio to Microsoft Power BI – Part 2: IAM-based domains</title>
		<link>https://noise.getoto.net/2026/09/15/connect-amazon-sagemaker-unified-studio-to-microsoft-power-bi-part-2-iam-based-domains/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Tue, 15 Sep 2026 20:55:16 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Connect Microsoft Power BI directly to governed data in Amazon SageMaker Unified Studio using the Amazon Athena ODBC driver. Part 2 covers IAM-based domains with SageMakerIam authentication, including AWS IAM Identity Center administrator setup, for both DSN-based and DSN-less connection methods.]]></description>
		
		
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		<item>
		<title>Track SageMaker Unified Studio project costs with custom tags and AWS CUR</title>
		<link>https://noise.getoto.net/2026/08/20/track-sagemaker-unified-studio-project-costs-with-custom-tags-and-aws-cur/</link>
		
		<dc:creator><![CDATA[Nisha Gambhir]]></dc:creator>
		<pubDate>Thu, 20 Aug 2026 16:19:24 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Learn how to track Amazon SageMaker Unified Studio project costs by custom tags. This serverless solution enriches AWS Cost and Usage Report (CUR) data with custom project tags and visualizes cost by CostCenter, Team, or Environment in an Amazon Quick Sight dashboard.]]></description>
		
		
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			</item>
		<item>
		<title>Secure SageMaker Unified Studio access with SAML and conditional policies</title>
		<link>https://noise.getoto.net/2026/08/19/secure-sagemaker-unified-studio-access-with-saml-and-conditional-policies/</link>
		
		<dc:creator><![CDATA[Manos Samatas]]></dc:creator>
		<pubDate>Wed, 19 Aug 2026 20:35:54 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Learn how to secure Amazon SageMaker Unified Studio by integrating it with an external SAML identity provider such as Okta. This post shows you how to apply conditional access policies that enforce device compliance, IP-based restrictions, and multi-factor authentication for your data and AI workloads.]]></description>
		
		
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			</item>
		<item>
		<title>Scaling fine-grained access control for enterprise lakehouse using SageMaker Unified Studio and AWS Lake Formation</title>
		<link>https://noise.getoto.net/2026/08/06/scaling-fine-grained-access-control-for-enterprise-lakehouse-using-sagemaker-unified-studio-and-aws-lake-formation/</link>
		
		<dc:creator><![CDATA[Chintan Agrawal]]></dc:creator>
		<pubDate>Thu, 06 Aug 2026 16:17:59 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[Customer Solutions]]></category>
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					<description><![CDATA[As enterprise lakehouses grow to thousands of tables across business domains and regions, fine-grained access control becomes a governance bottleneck. This post shows how to combine AWS IAM Identity Center, AWS Lake Formation tag-based access control, and trusted identity propagation in Amazon SageMaker Unified Studio for automated, auditable, least-privilege access.]]></description>
		
		
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			</item>
		<item>
		<title>Govern Amazon Redshift Data Warehouses Data Across Accounts using Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2026/07/20/govern-amazon-redshift-data-warehouses-data-across-accounts-using-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Bandana Das]]></dc:creator>
		<pubDate>Mon, 20 Jul 2026 16:48:33 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></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 use Amazon SageMaker Unified Studio to implement cross-account data sharing in Amazon Redshift using data mesh principles. We demonstrate how to build a scalable data mesh architecture that supports secure, auditable data sharing across AWS accounts while reducing operational burden.]]></description>
		
		
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			</item>
		<item>
		<title>Introducing Apache Spark Connect support in AWS Glue interactive sessions</title>
		<link>https://noise.getoto.net/2026/07/07/introducing-apache-spark-connect-support-in-aws-glue-interactive-sessions/</link>
		
		<dc:creator><![CDATA[Zach Mitchell]]></dc:creator>
		<pubDate>Tue, 07 Jul 2026 16:38:42 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Apache Spark Connect bridges the gap between these two worlds: you develop in local Python, but execute on AWS Glue against actual data. Today, AWS Glue interactive sessions support Spark Connect natively. You can connect from any environment that supports the PySpark remote() API, including VS Code, PyCharm, Amazon SageMaker Unified Studio notebooks, and standalone Python applications. You don’t need to install specialized kernels or manage cluster infrastructure.]]></description>
		
		
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			</item>
		<item>
		<title>Modernizing financial analytics with Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2026/06/22/modernizing-financial-analytics-with-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Umang Aggarwal]]></dc:creator>
		<pubDate>Mon, 22 Jun 2026 16:42:55 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS IAM Identity Center]]></category>
		<category><![CDATA[AWS Identity and Access Management (IAM)]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=afd764b970053657691acc95e0a86c02</guid>

					<description><![CDATA[Avanse Financial Services, India’s leading education loan providers, migrated to a cloud-native lakehouse architecture using Amazon SageMaker Unified Studio, which unified their data engineering, analytics, and artificial intelligence (AI) workflows in a single governed environment on AWS. In this post, we walk through their migration journey so you can adapt their approach to your own environment.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Detecting fraud patterns across Snowflake and AWS using SageMaker Data Agent</title>
		<link>https://noise.getoto.net/2026/06/22/detecting-fraud-patterns-across-snowflake-and-aws-using-sagemaker-data-agent/</link>
		
		<dc:creator><![CDATA[Akash Gupta]]></dc:creator>
		<pubDate>Mon, 22 Jun 2026 16:38:49 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=378aa1829a79b50b7af8233a4b42a1a6</guid>

					<description><![CDATA[Amazon SageMaker Data Agent launches three new capabilities in Amazon SageMaker Unified Studio notebooks: SQL analytics on Snowflake data sources, materialized view management, and interactive charting. Practitioners can use them together to query Snowflake alongside AWS data, pre-compute and schedule repeated aggregations, and create interactive visualizations from natural language prompts in a single notebook, without writing boilerplate code or switching tools. In this post, we describe the challenges these capabilities address, introduce each one, and walk through a fraud analytics scenario that demonstrates them working together in an end-to-end investigation workflow.]]></description>
		
		
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			</item>
		<item>
		<title>AI-assisted data development with Kiro and SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2026/06/16/ai-assisted-data-development-with-kiro-and-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Zach Mitchell]]></dc:creator>
		<pubDate>Tue, 16 Jun 2026 17:35:27 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Foundational (100)]]></category>
		<category><![CDATA[Kiro]]></category>
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					<description><![CDATA[With the AWS Toolkit for Visual Studio Code, you can connect Kiro, VS Code, or Cursor directly to Amazon SageMaker Unified Studio. This post demonstrates the integration using Kiro. The same Remote Access connection works with VS Code and Cursor. The post starts by showing what you can do with this integration: using natural language to explore and analyze data in a governed environment. We then walk through the setup so you can try it yourself.]]></description>
		
		
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			</item>
		<item>
		<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>
		
		
		<enclosure url="" length="0" type="" />

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

			</item>
		<item>
		<title>Schedule notebook runs in Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2026/06/03/schedule-notebook-runs-in-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Shivani Mehendarge]]></dc:creator>
		<pubDate>Wed, 03 Jun 2026 20:19:11 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we walk you through the new scheduling and orchestrating capabilities for notebooks in Amazon SageMaker Unified Studio.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</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>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=86194325156a26dca537f477601e3443</guid>

					<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>
		<item>
		<title>Automate deployment of data and AI applications with Amazon SageMaker Unified Studio CI/CD CLI</title>
		<link>https://noise.getoto.net/2026/05/21/automate-deployment-of-data-and-ai-applications-with-amazon-sagemaker-unified-studio-ci-cd-cli/</link>
		
		<dc:creator><![CDATA[Saurabh Bhutyani]]></dc:creator>
		<pubDate>Thu, 21 May 2026 19:13:50 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
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					<description><![CDATA[The CI/CD CLI for Amazon SageMaker Unified Studio (aws-smus-cicd-cli) is an open source command line tool that automates deployment of multi-service data and AI applications across pipeline stages. Data teams define their application once in a YAML manifest, DevOps teams deploy with a single command, and the CLI handles configuration substitution, dependency ordering, and resource provisioning automatically. In this post, we walk through how the CI/CD CLI works, show you how to deploy a real application across environments, and demonstrate how it fits into your existing CI/CD workflows.]]></description>
		
		
		<enclosure url="" length="0" type="" />

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		<item>
		<title>Capture data lineage of Amazon EMR spark jobs into Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2026/05/21/capture-data-lineage-of-amazon-emr-spark-jobs-into-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Jose Romero]]></dc:creator>
		<pubDate>Thu, 21 May 2026 17:49:27 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, you’ll walk through a practical, step-by-step example that shows how to capture and track data lineage from Spark jobs running on Amazon EMR directly into Amazon SageMaker Catalog using OpenLineage. You’ll see how lineage metadata flows automatically and explore data relationships and dependencies across your workflows in Amazon SageMaker Unified Studio.]]></description>
		
		
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