<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Sean Beath &#8211; Noise</title>
	<atom:link href="https://noise.getoto.net/author/sean-beath/feed/" rel="self" type="application/rss+xml" />
	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
	<lastBuildDate>Wed, 08 Feb 2023 17:42:23 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=6.8.2</generator>
	<item>
		<title>­­Use fuzzy string matching to approximate duplicate records in Amazon Redshift</title>
		<link>https://noise.getoto.net/2023/02/08/use-fuzzy-string-matching-to-approximate-duplicate-records-in-amazon-redshift/</link>
		
		<dc:creator><![CDATA[Sean Beath]]></dc:creator>
		<pubDate>Wed, 08 Feb 2023 17:42:23 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[serverless]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=c94d6f0277ce902dee492e349901b33a</guid>

					<description><![CDATA[It’s common to ingest multiple data sources into Amazon Redshift to perform analytics. Often, each data source will have its own processes of creating and maintaining data, which can lead to data quality challenges within and across sources. One challenge you may face when performing analytics is the presence of imperfect duplicate records within the source data. This post presents one possible approach to addressing this challenge in an Amazon Redshift data warehouse using fuzzy matching.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
	</channel>
</rss>

<!--
Performance optimized by W3 Total Cache. Learn more: https://www.boldgrid.com/w3-total-cache/

Object Caching 29/51 objects using Memcached
Page Caching using Disk: Enhanced 
Lazy Loading (feed)
Database Caching using Memcached

Served from: noise.getoto.net @ 2026-03-13 12:40:57 by W3 Total Cache
-->