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	<title>Raks Khare &#8211; Noise</title>
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	<description>The collective thoughts of the interwebz</description>
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		<title>Amazon Redshift Python user-defined functions will reach end of support after June 30, 2026</title>
		<link>https://noise.getoto.net/2025/06/30/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/</link>
		
		<dc:creator><![CDATA[Raks Khare]]></dc:creator>
		<pubDate>Mon, 30 Jun 2025 18:54:03 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[announcements]]></category>
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					<description><![CDATA[The Amazon Redshift integration with AWS Lambda provides the capability to create Amazon Redshift Lambda user-defined functions (UDFs). Because Lambda UDFs provide these significant advantages in integration, flexibility, scalability, and security, we will be ending support for Python UDFs in Amazon Redshift. In this post, we walk you through how to migrate your existing Python UDFs to Lambda UDFs, set up monitoring and cost evaluations, and review key considerations for a smooth transition.]]></description>
		
		
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		<title>Amazon Redshift announces history mode for zero-ETL integrations to simplify historical data tracking and analysis</title>
		<link>https://noise.getoto.net/2025/02/18/amazon-redshift-announces-history-mode-for-zero-etl-integrations-to-simplify-historical-data-tracking-and-analysis/</link>
		
		<dc:creator><![CDATA[Raks Khare]]></dc:creator>
		<pubDate>Tue, 18 Feb 2025 21:13:23 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[This post will explore brief history of zero-ETL, its importance for customers, and introduce an exciting new feature: history mode for Amazon Aurora PostgreSQL-Compatible Edition, Amazon Aurora MySQL-Compatible Edition, Amazon Relational Database Service (Amazon RDS) for MySQL, and Amazon DynamoDB zero-ETL integration with Amazon Redshift.]]></description>
		
		
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		<title>Develop a business chargeback model within your organization using Amazon Redshift multi-warehouse writes</title>
		<link>https://noise.getoto.net/2024/11/27/develop-a-business-chargeback-model-within-your-organization-using-amazon-redshift-multi-warehouse-writes/</link>
		
		<dc:creator><![CDATA[Raks Khare]]></dc:creator>
		<pubDate>Wed, 27 Nov 2024 20:22:50 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Now, we are announcing general availability (GA) of Amazon Redshift multi-data warehouse writes through data sharing. This new capability allows you to scale your write workloads and achieve better performance for extract, transform, and load (ETL) workloads by using different warehouses of different types and sizes based on your workload needs.]]></description>
		
		
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		<title>Incremental refresh for Amazon Redshift materialized views on data lake tables</title>
		<link>https://noise.getoto.net/2024/11/08/incremental-refresh-for-amazon-redshift-materialized-views-on-data-lake-tables/</link>
		
		<dc:creator><![CDATA[Raks Khare]]></dc:creator>
		<pubDate>Fri, 08 Nov 2024 14:55:27 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Amazon Redshift now provides the ability to incrementally refresh your materialized views on data lake tables including open file and table formats such as Apache Iceberg. In this post, we will show you step-by-step what operations are supported on both open file formats and transactional data lake tables to enable incremental refresh of the materialized view.]]></description>
		
		
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		<title>Simplify your query performance diagnostics in Amazon Redshift with Query profiler</title>
		<link>https://noise.getoto.net/2024/10/23/simplify-your-query-performance-diagnostics-in-amazon-redshift-with-query-profiler/</link>
		
		<dc:creator><![CDATA[Raks Khare]]></dc:creator>
		<pubDate>Wed, 23 Oct 2024 20:42:47 +0000</pubDate>
				<category><![CDATA[*Learning Levels]]></category>
		<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Amazon Redshift has introduced a new feature called the Query profiler. The Query profiler is a graphical tool that helps users analyze the components and performance of a query. This feature is part of the Amazon Redshift console and provides a visual and graphical representation of the query's run order, execution plan, and various statistics. The Query profiler makes it easier for users to understand and troubleshoot their queries. In this post, we cover two common use cases for troubleshooting query performance. We show you step-by-step how to analyze and troubleshoot long-running queries using the Query profiler.]]></description>
		
		
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		<title>Achieve near real time operational analytics using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift</title>
		<link>https://noise.getoto.net/2024/04/10/achieve-near-real-time-operational-analytics-using-amazon-aurora-postgresql-zero-etl-integration-with-amazon-redshift/</link>
		
		<dc:creator><![CDATA[Raks Khare]]></dc:creator>
		<pubDate>Wed, 10 Apr 2024 16:42:16 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Aurora]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Our zero-ETL integration with Amazon Redshift facilitates point-to-point data movement to get it ready for analytics, artificial intelligence (AI) and machine learning (ML) using Amazon Redshift on petabytes of data. In this post, we provide step-by-step guidance on how to get started with near real time operational analytics using the Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift.]]></description>
		
		
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		<title>Data load made easy and secure in Amazon Redshift using Query Editor V2</title>
		<link>https://noise.getoto.net/2023/05/02/data-load-made-easy-and-secure-in-amazon-redshift-using-query-editor-v2/</link>
		
		<dc:creator><![CDATA[Raks Khare]]></dc:creator>
		<pubDate>Tue, 02 May 2023 15:53:40 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to analyze all your data efficiently and securely. Users such as data analysts, database developers, and data scientists use SQL to analyze their data in Amazon Redshift data warehouses. Amazon Redshift provides a web-based Query Editor V2 in […]]]></description>
		
		
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		<title>Share and publish your Snowflake data to AWS Data Exchange using Amazon Redshift data sharing</title>
		<link>https://noise.getoto.net/2022/11/17/share-and-publish-your-snowflake-data-to-aws-data-exchange-using-amazon-redshift-data-sharing/</link>
		
		<dc:creator><![CDATA[Raks Khare]]></dc:creator>
		<pubDate>Thu, 17 Nov 2022 16:43:32 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Data Exchange]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[serverless]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. Today, tens of thousands of AWS customers—from Fortune 500 companies, startups, and everything in between—use Amazon Redshift to run mission-critical business intelligence (BI) dashboards, […]]]></description>
		
		
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		<title>Migrate from Snowflake to Amazon Redshift using AWS Glue Python shell</title>
		<link>https://noise.getoto.net/2022/06/28/migrate-from-snowflake-to-amazon-redshift-using-aws-glue-python-shell/</link>
		
		<dc:creator><![CDATA[Raks Khare]]></dc:creator>
		<pubDate>Tue, 28 Jun 2022 16:05:58 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Migration]]></category>
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					<description><![CDATA[As the most widely used cloud data warehouse, Amazon Redshift makes it simple and cost-effective to analyze your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. Tens of thousands of customers use Amazon Redshift to analyze exabytes of data per day and power analytics workloads […]]]></description>
		
		
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