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	<title>Navnit Shukla &#8211; Noise</title>
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		<title>Reference guide for building a self-service analytics solution with Amazon SageMaker</title>
		<link>https://noise.getoto.net/2025/12/16/reference-guide-for-building-a-self-service-analytics-solution-with-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Tue, 16 Dec 2025 21:47:23 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon SageMaker Data & AI Governance]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we show how to use Amazon SageMaker Catalog to publish data from multiple sources, including Amazon S3, Amazon Redshift, and Snowflake. This approach enables self-service access while ensuring robust data governance and metadata management.]]></description>
		
		
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		<title>Accelerate queries on Apache Iceberg tables through AWS Glue auto compaction</title>
		<link>https://noise.getoto.net/2024/12/19/accelerate-queries-on-apache-iceberg-tables-through-aws-glue-auto-compaction/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Thu, 19 Dec 2024 15:05:38 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Apache Iceberg]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
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					<description><![CDATA[In this post, we explore new features of the AWS Glue Data Catalog, which now supports improved automatic compaction of Iceberg tables for streaming data, making it straightforward for you to keep your transactional data lakes consistently performant. Enabling automatic compaction on Iceberg tables reduces metadata overhead on your Iceberg tables and improves query performance]]></description>
		
		
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		<title>A customer’s journey with Amazon OpenSearch Ingestion pipelines</title>
		<link>https://noise.getoto.net/2024/10/18/a-customers-journey-with-amazon-opensearch-ingestion-pipelines/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Fri, 18 Oct 2024 16:26:08 +0000</pubDate>
				<category><![CDATA[Amazon OpenSearch Service]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Customer Solutions]]></category>
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					<description><![CDATA[In this post, we share the journey of a multi-national financial credit reporting company, including the hurdles they faced, and why they went with Amazon OpenSearch Ingestion pipelines to make their log management smoother.]]></description>
		
		
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		<title>Revolutionizing data querying: Amazon Redshift and Visual Studio Code integration</title>
		<link>https://noise.getoto.net/2024/05/02/revolutionizing-data-querying-amazon-redshift-and-visual-studio-code-integration/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Thu, 02 May 2024 16:09:59 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[In today’s data-driven landscape, the efficiency and accessibility of querying tools play a crucial role in driving businesses forward. Amazon Redshift recently announced integration with Visual Studio Code (), an action that transforms the way data practitioners engage with Amazon Redshift and reshapes your interactions and practices in data management. This innovation not only unlocks […]]]></description>
		
		
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		<title>Process and analyze highly nested and large XML files using AWS Glue and Amazon Athena</title>
		<link>https://noise.getoto.net/2023/09/29/process-and-analyze-highly-nested-and-large-xml-files-using-aws-glue-and-amazon-athena/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Fri, 29 Sep 2023 15:43:12 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In today’s digital age, data is at the heart of every organization’s success. One of the most commonly used formats for exchanging data is XML. Analyzing XML files is crucial for several reasons. Firstly, XML files are used in many industries, including finance, healthcare, and government. Analyzing XML files can help organizations gain insights into […]]]></description>
		
		
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		<title>Set up advanced rules to validate quality of multiple datasets with AWS Glue Data Quality</title>
		<link>https://noise.getoto.net/2023/06/06/set-up-advanced-rules-to-validate-quality-of-multiple-datasets-with-aws-glue-data-quality/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Tue, 06 Jun 2023 15:59:21 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
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					<description><![CDATA[Data is the lifeblood of modern businesses. In today’s data-driven world, companies rely on data to make informed decisions, gain a competitive edge, and provide exceptional customer experiences. However, not all data is created equal. Poor-quality data can lead to incorrect insights, bad decisions, and lost opportunities. AWS Glue Data Quality measures and monitors the […]]]></description>
		
		
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		<title>Extract ServiceNow data using AWS Glue Studio in an Amazon S3 data lake and analyze using Amazon Athena</title>
		<link>https://noise.getoto.net/2022/02/10/extract-servicenow-data-using-aws-glue-studio-in-an-amazon-s3-data-lake-and-analyze-using-amazon-athena/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Thu, 10 Feb 2022 21:29:22 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
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					<description><![CDATA[Many different cloud-based software as a service (SaaS) offerings are available in AWS. ServiceNow is one of the common cloud-based workflow automation platforms widely used by AWS customers. In the past few years, we saw a lot of customers who wanted to extract and integrate data from IT service management (ITSM) tools like ServiceNow for […]]]></description>
		
		
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		<title>Enforce customized data quality rules in AWS Glue DataBrew</title>
		<link>https://noise.getoto.net/2021/11/25/enforce-customized-data-quality-rules-in-aws-glue-databrew/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Wed, 24 Nov 2021 23:23:24 +0000</pubDate>
				<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Glue DataBrew]]></category>
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					<description><![CDATA[GIGO (garbage in, garbage out) is a concept common to computer science and mathematics: the quality of the output is determined by the quality of the input. In modern data architecture, you bring data from different data sources, which creates challenges around volume, velocity, and veracity. You might write unit tests for applications, but it’s […]]]></description>
		
		
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		<title>Query SAP HANA using Athena Federated Query and join with data in your Amazon S3 data lake</title>
		<link>https://noise.getoto.net/2021/08/18/query-sap-hana-using-athena-federated-query-and-join-with-data-in-your-amazon-s3-data-lake/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Wed, 18 Aug 2021 20:15:29 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[database]]></category>
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					<description><![CDATA[If you use data lakes in Amazon Simple Storage Service (Amazon S3) and use SAP HANA as your transactional data store, you may need to join the data in your data lake with SAP HANA in the cloud, SAP HANA running on Amazon Elastic Compute Cloud (Amazon EC2), or with an on-premises SAP HANA, for […]]]></description>
		
		
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		<item>
		<title>Query a Teradata database using Amazon Athena Federated Query and join with data in your Amazon S3 data lake</title>
		<link>https://noise.getoto.net/2021/07/20/query-a-teradata-database-using-amazon-athena-federated-query-and-join-with-data-in-your-amazon-s3-data-lake/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Tue, 20 Jul 2021 20:12:38 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[database]]></category>
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					<description><![CDATA[If you use data lakes in Amazon Simple Storage Service (Amazon S3) and use Teradata as your transactional data store, you may need to join the data in your data lake with Teradata in the cloud, Teradata running on Amazon Elastic Compute Cloud (Amazon EC2), or with an on-premises Teradata database, for example to build […]]]></description>
		
		
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		<item>
		<title>Query Snowflake using Athena Federated Query and join with data in your Amazon S3 data lake</title>
		<link>https://noise.getoto.net/2021/07/15/query-snowflake-using-athena-federated-query-and-join-with-data-in-your-amazon-s3-data-lake/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Thu, 15 Jul 2021 19:38:16 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[database]]></category>
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					<description><![CDATA[If you use data lakes in Amazon Simple Storage Service (Amazon S3) and use Snowflake as your data warehouse solution, you may need to join your data in your data lake with Snowflake. For example, you may want to build a dashboard by joining historical data in your Amazon S3 data lake and the latest […]]]></description>
		
		
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		<title>Query your Oracle database using Athena Federated Query and join with data in your Amazon S3 data lake</title>
		<link>https://noise.getoto.net/2021/07/13/query-your-oracle-database-using-athena-federated-query-and-join-with-data-in-your-amazon-s3-data-lake/</link>
		
		<dc:creator><![CDATA[Navnit Shukla]]></dc:creator>
		<pubDate>Tue, 13 Jul 2021 17:26:24 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon RDS]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[RDS for Oracle]]></category>
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					<description><![CDATA[If you use data lakes in Amazon Simple Storage Service (Amazon S3) and use Oracle as your transactional data store, you may need to join the data in your data lake with Oracle on Amazon Relational Database Service (Amazon RDS), Oracle running on Amazon Elastic Compute Cloud (Amazon EC2), or an on-premises Oracle database, for […]]]></description>
		
		
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