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	<title>Arun A K &#8211; Noise</title>
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		<title>Enable strategic data quality management with AWS Glue DQDL labels</title>
		<link>https://noise.getoto.net/2026/01/26/enable-strategic-data-quality-management-with-aws-glue-dqdl-labels/</link>
		
		<dc:creator><![CDATA[Arun A K]]></dc:creator>
		<pubDate>Mon, 26 Jan 2026 17:42:05 +0000</pubDate>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[AWS Glue DQDL labels add organizational context to data quality management by attaching business metadata directly to validation rules. In this post, we highlight the new DQDL labels feature, which enhances how you organize, prioritize, and operationalize your data quality efforts at scale. We show how labels such as business criticality, compliance requirements, team ownership, or data domain can be attached to data quality rules to streamline triage and analysis. You’ll learn how to quickly surface targeted insights (for example, “all high-priority customer data failures owned by marketing” or “GDPR-related issues from our Salesforce ingestion pipeline”) and how DQDL labels can help teams improve accountability and accelerate remediation workflows.]]></description>
		
		
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		<title>Configure seamless single sign-on with SQL analytics in Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2025/10/18/configure-seamless-single-sign-on-with-sql-analytics-in-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Arun A K]]></dc:creator>
		<pubDate>Fri, 17 Oct 2025 23:20:34 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
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					<description><![CDATA[This post demonstrates how to configure SageMaker Unified Studio with SSO, set up projects and user onboarding, and access data securely using integrated analytics tools.]]></description>
		
		
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		<title>Interactively develop your AWS Glue streaming ETL jobs using AWS Glue Studio notebooks</title>
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		<dc:creator><![CDATA[Arun A K]]></dc:creator>
		<pubDate>Thu, 01 Sep 2022 18:43:52 +0000</pubDate>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[jupyternotebook]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Enterprise customers are modernizing their data warehouses and data lakes to provide real-time insights, because having the right insights at the right time is crucial for good business outcomes. To enable near-real-time decision-making, data pipelines need to process real-time or near-real-time data. This data is sourced from IoT devices, change data capture (CDC) services like […]]]></description>
		
		
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