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	<title>data governance &#8211; Noise</title>
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		<title>Breaking down data silos: Volkswagen’s approach with Amazon DataZone</title>
		<link>https://noise.getoto.net/2025/10/07/breaking-down-data-silos-volkswagens-approach-with-amazon-datazone/</link>
		
		<dc:creator><![CDATA[Bandana Das]]></dc:creator>
		<pubDate>Tue, 07 Oct 2025 17:28:21 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Automotive]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[data governance]]></category>
		<category><![CDATA[data-mesh]]></category>
		<category><![CDATA[Manufacturing]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we introduce Amazon DataZone and explore how Volkswagen used Amazon DataZone to build their data mesh, tackle the challenges encountered, and break the data silos.]]></description>
		
		
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		<item>
		<title>Guide to adopting Amazon SageMaker Unified Studio from ATPCO’s Journey</title>
		<link>https://noise.getoto.net/2025/08/18/guide-to-adopting-amazon-sagemaker-unified-studio-from-atpcos-journey/</link>
		
		<dc:creator><![CDATA[Mitesh Patel]]></dc:creator>
		<pubDate>Mon, 18 Aug 2025 19:03:39 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[data governance]]></category>
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					<description><![CDATA[ATPCO is the backbone of modern airline retailing, helping airlines and third-party channels deliver the right offers to customers at the right time. ATPCO addressed data governance challenges using Amazon DataZone. SageMaker Unified Studio, built on the same architecture as Amazon DataZone, offers additional capabilities, so users can complete various tasks such as building data pipelines using AWS Glue and Amazon EMR, or conducting analyses using Amazon Athena and Amazon Redshift query editor across diverse datasets, all within a single, unified environment. In this post, we walk you through the challenges ATPCO addresses for their business using SageMaker Unified Studio.]]></description>
		
		
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		<item>
		<title>Accelerate your data quality journey for lakehouse architecture with Amazon SageMaker, Apache Iceberg on AWS, Amazon S3 tables, and AWS Glue Data Quality</title>
		<link>https://noise.getoto.net/2025/07/28/accelerate-your-data-quality-journey-for-lakehouse-architecture-with-amazon-sagemaker-apache-iceberg-on-aws-amazon-s3-tables-and-aws-glue-data-quality/</link>
		
		<dc:creator><![CDATA[Brody Pearman]]></dc:creator>
		<pubDate>Mon, 28 Jul 2025 18:09:37 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Glue Data Quality]]></category>
		<category><![CDATA[data governance]]></category>
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					<description><![CDATA[This post explores how you can use AWS Glue Data Quality to maintain data quality of S3 Tables and Apache Iceberg tables on general purpose S3 buckets. We'll discuss strategies for verifying the quality of published data and how these integrated technologies can be used to implement effective data quality workflows.]]></description>
		
		
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		<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>
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					<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>
		
		
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		<title>How EUROGATE established a data mesh architecture using Amazon DataZone</title>
		<link>https://noise.getoto.net/2025/01/15/how-eurogate-established-a-data-mesh-architecture-using-amazon-datazone/</link>
		
		<dc:creator><![CDATA[Dr. Leonard Heilig]]></dc:creator>
		<pubDate>Wed, 15 Jan 2025 17:37:44 +0000</pubDate>
				<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[data governance]]></category>
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					<description><![CDATA[In this post, we show you how EUROGATE uses AWS services, including Amazon DataZone, to make data discoverable by data consumers across different business units so that they can innovate faster. Two use cases illustrate how this can be applied for business intelligence (BI) and data science applications, using AWS services such as Amazon Redshift and Amazon SageMaker.]]></description>
		
		
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			</item>
		<item>
		<title>Seamless integration of data lake and data warehouse using Amazon Redshift Spectrum and Amazon DataZone</title>
		<link>https://noise.getoto.net/2024/08/15/seamless-integration-of-data-lake-and-data-warehouse-using-amazon-redshift-spectrum-and-amazon-datazone/</link>
		
		<dc:creator><![CDATA[Lakshmi Nair]]></dc:creator>
		<pubDate>Thu, 15 Aug 2024 16:18:49 +0000</pubDate>
				<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon Redshift Spectrum]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[data governance]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Unlocking the true value of data often gets impeded by siloed information. Traditional data management—wherein each business unit ingests raw data in separate data lakes or warehouses—hinders visibility and cross-functional analysis. A data mesh framework empowers business units with data ownership and facilitates seamless sharing. However, integrating datasets from different business units can present several […]]]></description>
		
		
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			</item>
		<item>
		<title>Implement data quality checks on Amazon Redshift data assets and integrate with Amazon DataZone</title>
		<link>https://noise.getoto.net/2024/08/15/implement-data-quality-checks-on-amazon-redshift-data-assets-and-integrate-with-amazon-datazone/</link>
		
		<dc:creator><![CDATA[Lakshmi Nair]]></dc:creator>
		<pubDate>Thu, 15 Aug 2024 16:16:22 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Glue Data Quality]]></category>
		<category><![CDATA[data governance]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we show how to capture the data quality metrics for data assets produced in Amazon Redshift. With Amazon DataZone, the data owner can directly import the technical metadata of a Redshift database table and views to the Amazon DataZone project’s inventory. As these data assets gets imported into Amazon DataZone, it bypasses the AWS Glue Data Catalog, creating a gap in data quality integration. This post proposes a solution to enrich the Amazon Redshift data asset with data quality scores and KPI metrics.]]></description>
		
		
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			</item>
		<item>
		<title>Streamline your data governance by deploying Amazon DataZone with the AWS CDK</title>
		<link>https://noise.getoto.net/2024/07/23/streamline-your-data-governance-by-deploying-amazon-datazone-with-the-aws-cdk/</link>
		
		<dc:creator><![CDATA[Bandana Das]]></dc:creator>
		<pubDate>Tue, 23 Jul 2024 17:07:36 +0000</pubDate>
				<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[AWS CDK]]></category>
		<category><![CDATA[AWS Cloud Development Kit]]></category>
		<category><![CDATA[data governance]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=791d39bf39ec75c571aa8e212d96c3a9</guid>

					<description><![CDATA[Managing data across diverse environments can be a complex and daunting task. Amazon DataZone simplifies this so you can catalog, discover, share, and govern data stored across AWS, on premises, and third-party sources. Many organizations manage vast amounts of data assets owned by various teams, creating a complex landscape that poses challenges for scalable data […]]]></description>
		
		
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		<item>
		<title>Deploy DataHub using AWS managed services and ingest metadata from AWS Glue and Amazon Redshift – Part 2</title>
		<link>https://noise.getoto.net/2022/10/25/deploy-datahub-using-aws-managed-services-and-ingest-metadata-from-aws-glue-and-amazon-redshift-part-2/</link>
		
		<dc:creator><![CDATA[Corvus Lee]]></dc:creator>
		<pubDate>Tue, 25 Oct 2022 16:22:18 +0000</pubDate>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[data governance]]></category>
		<category><![CDATA[DataHub]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[metadata management]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In the first post of this series, we discussed the need of a metadata management solution for organizations. We used DataHub as an open-source metadata platform for metadata management and deployed it using AWS managed services with the AWS Cloud Development Kit (AWS CDK). In this post, we focus on how to populate technical metadata […]]]></description>
		
		
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			</item>
		<item>
		<title>Deploy DataHub using AWS managed services and ingest metadata from AWS Glue and Amazon Redshift – Part 1</title>
		<link>https://noise.getoto.net/2022/10/25/deploy-datahub-using-aws-managed-services-and-ingest-metadata-from-aws-glue-and-amazon-redshift-part-1/</link>
		
		<dc:creator><![CDATA[Debadatta Mohapatra]]></dc:creator>
		<pubDate>Tue, 25 Oct 2022 16:20:31 +0000</pubDate>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[data governance]]></category>
		<category><![CDATA[DataHub]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[metadata management]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Many organizations are establishing enterprise data warehouses, data lakes, or a modern data architecture on AWS to build data-driven products. As the organization grows, the number of publishers and subscribers to data and the volume of data keeps increasing. Additionally, different varieties of datasets are introduced (structured, semistructured, and unstructured). This can lead to metadata […]]]></description>
		
		
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