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	<title>Amazon Athena &#8211; Noise</title>
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		<title>Amazon S3 Storage Lens adds performance metrics, support for billions of prefixes, and export to S3 Tables</title>
		<link>https://noise.getoto.net/2025/12/02/amazon-s3-storage-lens-adds-performance-metrics-support-for-billions-of-prefixes-and-export-to-s3-tables/</link>
		
		<dc:creator><![CDATA[Veliswa Boya]]></dc:creator>
		<pubDate>Tue, 02 Dec 2025 16:15:12 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon CloudWatch]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon QuickSight]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon S3 Tables]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[storage]]></category>
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					<description><![CDATA[New capabilities help optimize application performance, analyze unlimited prefixes, and simplify metrics analysis through S3 Tables integration.]]></description>
		
		
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		<item>
		<title>Amazon FSx for NetApp ONTAP now integrates with Amazon S3 for seamless data access</title>
		<link>https://noise.getoto.net/2025/12/02/amazon-fsx-for-netapp-ontap-now-integrates-with-amazon-s3-for-seamless-data-access/</link>
		
		<dc:creator><![CDATA[Veliswa Boya]]></dc:creator>
		<pubDate>Tue, 02 Dec 2025 15:59:54 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon FSx for NetApp ONTAP]]></category>
		<category><![CDATA[Amazon Kinesis]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Compute]]></category>
		<category><![CDATA[serverless]]></category>
		<category><![CDATA[storage]]></category>
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					<description><![CDATA[Access FSx for NetApp ONTAP file data through S3 to enable AI/ML workloads and analytics—letting you use enterprise file data with Bedrock, SageMaker, and analytics services while it remains in your file system.]]></description>
		
		
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			</item>
		<item>
		<title>Orchestrating big data processing with AWS Step Functions Distributed Map</title>
		<link>https://noise.getoto.net/2025/11/05/orchestrating-big-data-processing-with-aws-step-functions-distributed-map/</link>
		
		<dc:creator><![CDATA[Biswanath Mukherjee]]></dc:creator>
		<pubDate>Tue, 04 Nov 2025 23:42:01 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, you'll learn how to use AWS Step Functions Distributed Map to process Amazon Athena data manifest and Parquet files through a step-by-step demonstration.]]></description>
		
		
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			</item>
		<item>
		<title>How Twilio built a multi-engine query platform using Amazon Athena and open-source Presto</title>
		<link>https://noise.getoto.net/2025/10/21/how-twilio-built-a-multi-engine-query-platform-using-amazon-athena-and-open-source-presto/</link>
		
		<dc:creator><![CDATA[Amber Runnels]]></dc:creator>
		<pubDate>Tue, 21 Oct 2025 20:57:32 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Presto]]></category>
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					<description><![CDATA[At Twilio, we manage a 20 petabyte-scale Amazon S3 data lake that serves the analytics needs of over 1,500 users, processing 2.5 million queries monthly and scanning an average of 85 PB of data. To meet our growing demands for scalability, emerging technology support, and data mesh architecture adoption, we built Odin, a multi-engine query platform that provides an abstraction layer built on top of Presto Gateway. In this post, we discuss how we designed and built Odin, combining Amazon Athena with open-source Presto to create a flexible, scalable data querying solution.]]></description>
		
		
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			</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>
		
		
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			</item>
		<item>
		<title>Transform your data to Amazon S3 Tables with Amazon Athena</title>
		<link>https://noise.getoto.net/2025/08/15/transform-your-data-to-amazon-s3-tables-with-amazon-athena/</link>
		
		<dc:creator><![CDATA[Pathik Shah]]></dc:creator>
		<pubDate>Fri, 15 Aug 2025 20:25:21 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon S3 Tables]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=9f310f2a619c50a975e7ea46bf2ec8d3</guid>

					<description><![CDATA[This post demonstrates how Amazon Athena CREATE TABLE AS SELECT (CTAS) simplifies the data transformation process through a practical example: migrating an existing Parquet dataset into Amazon S3 Tables.]]></description>
		
		
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			</item>
		<item>
		<title>Build an analytics pipeline that is resilient to Avro schema changes using Amazon Athena</title>
		<link>https://noise.getoto.net/2025/07/25/build-an-analytics-pipeline-that-is-resilient-to-avro-schema-changes-using-amazon-athena/</link>
		
		<dc:creator><![CDATA[Mohammad Sabeel]]></dc:creator>
		<pubDate>Fri, 25 Jul 2025 16:33:06 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=60f1626244e9a4ca8d6fab8d53784395</guid>

					<description><![CDATA[This post demonstrates how to build a solution by combining Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue Data Catalog for schema management, and Amazon Athena for one-time querying. We'll focus specifically on handling Avro-formatted data in partitioned S3 buckets, where schemas can change frequently while providing consistent query capabilities across all data regardless of schema versions.]]></description>
		
		
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			</item>
		<item>
		<title>How Stifel built a modern data platform using AWS Glue and an event-driven domain architecture</title>
		<link>https://noise.getoto.net/2025/07/07/how-stifel-built-a-modern-data-platform-using-aws-glue-and-an-event-driven-domain-architecture/</link>
		
		<dc:creator><![CDATA[Amit Maindola]]></dc:creator>
		<pubDate>Mon, 07 Jul 2025 14:22:19 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EventBridge]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Experience-Based Acceleration]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<category><![CDATA[Thought Leadership]]></category>
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					<description><![CDATA[In this post, we show you how Stifel implemented a modern data platform using AWS services and open data standards, building an event-driven architecture for domain data products while centralizing the metadata to facilitate discovery and sharing of data products.]]></description>
		
		
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			</item>
		<item>
		<title>AWS Weekly Roundup: New AWS Heroes, Amazon Q Developer, EC2 GPU price reduction, and more (June 9, 2025)</title>
		<link>https://noise.getoto.net/2025/06/09/aws-weekly-roundup-new-aws-heroes-amazon-q-developer-ec2-gpu-price-reduction-and-more-june-9-2025/</link>
		
		<dc:creator><![CDATA[Betty Zheng (郑予彬)]]></dc:creator>
		<pubDate>Mon, 09 Jun 2025 17:34:46 +0000</pubDate>
				<category><![CDATA[Amazon API Gateway]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EC2]]></category>
		<category><![CDATA[Amazon Elastic Kubernetes Service]]></category>
		<category><![CDATA[Amazon Q Developer]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Heroes]]></category>
		<category><![CDATA[AWS Network Firewall]]></category>
		<category><![CDATA[Graviton]]></category>
		<category><![CDATA[Week in Review]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=4a20b5aaa5bebe64c02610c1ee3ba2d0</guid>

					<description><![CDATA[The AWS Heroes program recognizes a vibrant, worldwide group of AWS experts whose enthusiasm for knowledge-sharing has a real impact within the community. Heroes go above and beyond to share knowledge in a variety of ways in developer community. We introduce our newest AWS Heroes in the second quarter of 2025. To find and connect […]]]></description>
		
		
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			</item>
		<item>
		<title>Introducing managed query results for Amazon Athena</title>
		<link>https://noise.getoto.net/2025/06/03/introducing-managed-query-results-for-amazon-athena/</link>
		
		<dc:creator><![CDATA[Guy Bachar]]></dc:creator>
		<pubDate>Tue, 03 Jun 2025 20:40:21 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[announcements]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=cb542d243e36a8d1a97e0df8706eb409</guid>

					<description><![CDATA[We’re thrilled to introduce managed query results, a new Athena feature that automatically stores, secures, and manages the lifecycle of query result data for you at no additional cost. In this post, we demonstrate how to get started with managed query results and, by removing the undifferentiated effort spent on query result management, how Athena helps you get insights from your data in fewer steps than before.]]></description>
		
		
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			</item>
		<item>
		<title>Build a secure serverless streaming pipeline with Amazon MSK Serverless, Amazon EMR Serverless and IAM</title>
		<link>https://noise.getoto.net/2025/06/02/build-a-secure-serverless-streaming-pipeline-with-amazon-msk-serverless-amazon-emr-serverless-and-iam/</link>
		
		<dc:creator><![CDATA[Shubham Purwar]]></dc:creator>
		<pubDate>Mon, 02 Jun 2025 14:45:04 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Managed Streaming for Apache Kafka (Amazon MSK)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=b1a37828eb0f71d100b2054b91dfd2a3</guid>

					<description><![CDATA[The post demonstrates a comprehensive, end-to-end solution for processing data from MSK Serverless using an EMR Serverless Spark Streaming job, secured with IAM authentication. Additionally, it demonstrates how to query the processed data using Amazon Athena, providing a seamless and integrated workflow for data processing and analysis. This solution enables near real-time querying of the latest data processed from MSK Serverless and EMR Serverless using Athena, providing instant insights and analytics.]]></description>
		
		
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		<item>
		<title>Configure cross-account access of Amazon SageMaker Lakehouse multi-catalog tables using AWS Glue 5.0 Spark</title>
		<link>https://noise.getoto.net/2025/05/09/configure-cross-account-access-of-amazon-sagemaker-lakehouse-multi-catalog-tables-using-aws-glue-5-0-spark/</link>
		
		<dc:creator><![CDATA[Aarthi Srinivasan]]></dc:creator>
		<pubDate>Fri, 09 May 2025 17:18:44 +0000</pubDate>
				<category><![CDATA[*Learning Levels]]></category>
		<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Apache Iceberg]]></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=cc26012180b2a67d5ac39577ed6929eb</guid>

					<description><![CDATA[In this post, we show you how to share an Amazon Redshift table and Amazon S3 based Iceberg table from the account that owns the data to another account that consumes the data. In the recipient account, we run a join query on the shared data lake and data warehouse tables using Spark in AWS Glue 5.0. We walk you through the complete cross-account setup and provide the Spark configuration in a Python notebook.]]></description>
		
		
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		<item>
		<title>How BMW Group built a serverless terabyte-scale data transformation architecture with dbt and Amazon Athena</title>
		<link>https://noise.getoto.net/2025/04/29/how-bmw-group-built-a-serverless-terabyte-scale-data-transformation-architecture-with-dbt-and-amazon-athena/</link>
		
		<dc:creator><![CDATA[Philipp Karg]]></dc:creator>
		<pubDate>Tue, 29 Apr 2025 16:35:40 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon QuickSight]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=e3c8a1aea4310da953cbf3f425dbc8ac</guid>

					<description><![CDATA[At the BMW Group, our Cloud Efficiency Analytics (CLEA) team has developed a FinOps solution to optimize costs across over 10,000 cloud accounts This post explores our journey, from the initial challenges to our current architecture, and details the steps we took to achieve a highly efficient, serverless data transformation setup.]]></description>
		
		
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		<item>
		<title>Amazon SageMaker Lakehouse now supports attribute-based access control</title>
		<link>https://noise.getoto.net/2025/04/24/amazon-sagemaker-lakehouse-now-supports-attribute-based-access-control/</link>
		
		<dc:creator><![CDATA[Sandeep Adwankar]]></dc:creator>
		<pubDate>Thu, 24 Apr 2025 20:16:32 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon S3]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Identity and Access Management (IAM)]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=fdcb8abb606391792379f8dd4550f5ec</guid>

					<description><![CDATA[Amazon SageMaker Lakehouse now supports attribute-based access control (ABAC) with AWS Lake Formation, using AWS Identity and Access Management (IAM) principals and session tags to simplify data access, grant creation, and maintenance. In this post, we demonstrate how to get started with SageMaker Lakehouse with ABAC.]]></description>
		
		
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		<item>
		<title>Read and write Apache Iceberg tables using AWS Lake Formation hybrid access mode</title>
		<link>https://noise.getoto.net/2025/04/21/read-and-write-apache-iceberg-tables-using-aws-lake-formation-hybrid-access-mode/</link>
		
		<dc:creator><![CDATA[Aarthi Srinivasan]]></dc:creator>
		<pubDate>Mon, 21 Apr 2025 17:10:48 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[AWS Analytics]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=ea72e3b07988c055c2768739b153e1a3</guid>

					<description><![CDATA[In this post, we demonstrate how to use Lake Formation for read access while continuing to use AWS Identity and Access Management (IAM) policy-based permissions for write workloads that update the schema and upsert (insert and update combined) data records into the Iceberg tables.]]></description>
		
		
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		<item>
		<title>Accelerate your analytics with Amazon S3 Tables and Amazon SageMaker Lakehouse</title>
		<link>https://noise.getoto.net/2025/04/17/accelerate-your-analytics-with-amazon-s3-tables-and-amazon-sagemaker-lakehouse/</link>
		
		<dc:creator><![CDATA[Sandeep Adwankar]]></dc:creator>
		<pubDate>Thu, 17 Apr 2025 20:31:07 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Identity and Access Management (IAM)]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=3f509fa8a8e4dc0a5661cc6515d4798c</guid>

					<description><![CDATA[Amazon SageMaker Lakehouse is a unified, open, and secure data lakehouse that now seamlessly integrates with Amazon S3 Tables, the first cloud object store with built-in Apache Iceberg support. In this post, we guide you how to use various analytics services using the integration of SageMaker Lakehouse with S3 Tables.]]></description>
		
		
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		<item>
		<title>Enhancing Adobe Marketo Engage Data Analysis with AWS Glue Integration</title>
		<link>https://noise.getoto.net/2025/03/11/enhancing-adobe-marketo-engage-data-analysis-with-aws-glue-integration/</link>
		
		<dc:creator><![CDATA[Kenny Rajan]]></dc:creator>
		<pubDate>Tue, 11 Mar 2025 18:28:49 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Partner solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=1382a6f6d87aa669c392d77b7538c0db</guid>

					<description><![CDATA[In this post, we show you how to use AWS Glue to extract data from Marketo Engage for data processing and enrichment on AWS for use in marketing analytics workflows.]]></description>
		
		
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		<item>
		<title>Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity</title>
		<link>https://noise.getoto.net/2024/12/16/introducing-a-new-unified-data-connection-experience-with-amazon-sagemaker-lakehouse-unified-data-connectivity/</link>
		
		<dc:creator><![CDATA[Chiho Sugimoto]]></dc:creator>
		<pubDate>Mon, 16 Dec 2024 15:08:31 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=970af3d7c5f44b0d8378fd4129b43a40</guid>

					<description><![CDATA[With Amazon SageMaker Lakehouse unified data connectivity, you can confidently connect, explore, and unlock the full value of your data across AWS services and achieve your business objectives with agility. This post demonstrates how SageMaker Lakehouse unified data connectivity helps your data integration workload by streamlining the establishment and management of connections for various data sources.]]></description>
		
		
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		<item>
		<title>Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt</title>
		<link>https://noise.getoto.net/2024/12/12/building-end-to-end-data-lineage-for-one-time-and-complex-queries-using-amazon-athena-amazon-redshift-amazon-neptune-and-dbt/</link>
		
		<dc:creator><![CDATA[Nancy Wu]]></dc:creator>
		<pubDate>Thu, 12 Dec 2024 17:17:33 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon Neptune]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon S3]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=31bb9de5175a42447654408fbe5a1009</guid>

					<description><![CDATA[In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. dbt on Athena supports real-time queries, while dbt on Amazon Redshift handles complex queries, unifying the development language and significantly reducing the technical learning curve. Using a single dbt modeling language not only simplifies the development process but also automatically generates consistent data lineage information. This approach offers robust adaptability, easily accommodating changes in data structures.]]></description>
		
		
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			</item>
		<item>
		<title>Catalog and govern Amazon Athena federated queries with Amazon SageMaker Lakehouse</title>
		<link>https://noise.getoto.net/2024/12/04/catalog-and-govern-amazon-athena-federated-queries-with-amazon-sagemaker-lakehouse/</link>
		
		<dc:creator><![CDATA[Sandeep Adwankar]]></dc:creator>
		<pubDate>Wed, 04 Dec 2024 18:34:29 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Analytics]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=148b7a347398be9f28b749740237b168</guid>

					<description><![CDATA[In this post, we show how to connect to, govern, and run federated queries on data stored in Redshift, DynamoDB (Preview), and Snowflake (Preview). To query our data, we use Athena, which is seamlessly integrated with SageMaker Unified Studio. We use SageMaker Lakehouse to present data to end-users as federated catalogs, a new type of catalog object. Finally, we demonstrate how to use column-level security permissions in AWS Lake Formation to give analysts access to the data they need while restricting access to sensitive information.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
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