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	<title>Shubham Purwar &#8211; Noise</title>
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		<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>
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		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
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					<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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		<title>Build a secure serverless streaming pipeline with Amazon MSK Serverless, Amazon EMR Serverless and IAM</title>
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		<dc:creator><![CDATA[Shubham Purwar]]></dc:creator>
		<pubDate>Mon, 02 Jun 2025 14:45:04 +0000</pubDate>
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					<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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		<title>Synchronize data lakes with CDC-based UPSERT using open table format, AWS Glue, and Amazon MSK</title>
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		<dc:creator><![CDATA[Shubham Purwar]]></dc:creator>
		<pubDate>Wed, 31 Jul 2024 19:27:55 +0000</pubDate>
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					<description><![CDATA[The post illustrates the construction of a comprehensive CDC system, enabling the processing of CDC data sourced from Amazon Relational Database Service (Amazon RDS) for MySQL. Initially, we’re creating a raw data lake of all modified records in the database in near real time using Amazon MSK and writing to Amazon S3 as raw data. Later, we use an AWS Glue exchange, transform, and load (ETL) job for batch processing of CDC data from the S3 raw data lake.]]></description>
		
		
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		<title>Securely process near-real-time data from Amazon MSK Serverless using an AWS Glue streaming ETL job with IAM authentication</title>
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		<dc:creator><![CDATA[Shubham Purwar]]></dc:creator>
		<pubDate>Wed, 13 Sep 2023 14:44:57 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Managed Streaming for Apache Kafka (Amazon MSK)]]></category>
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		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Streaming data has become an indispensable resource for organizations worldwide because it offers real-time insights that are crucial for data analytics. The escalating velocity and magnitude of collected data has created a demand for real-time analytics. This data originates from diverse sources, including social media, sensors, logs, and clickstreams, among others. With streaming data, organizations […]]]></description>
		
		
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