<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data Science on The Textsmith Magazine</title><link>https://magazine.thetextsmith.com/tags/data-science/</link><description>Recent content in Data Science on The Textsmith Magazine</description><generator>Hugo</generator><language>en-gb</language><lastBuildDate>Sat, 01 Aug 2026 07:14:47 +0200</lastBuildDate><atom:link href="https://magazine.thetextsmith.com/tags/data-science/index.xml" rel="self" type="application/rss+xml"/><item><title>What is Data Analysis, Really?</title><link>https://magazine.thetextsmith.com/data-analysis/what-is-data-analysis-really/</link><pubDate>Sat, 01 Aug 2026 07:14:47 +0200</pubDate><guid>https://magazine.thetextsmith.com/data-analysis/what-is-data-analysis-really/</guid><description>Data analysis is at the core of any industry pipeline these days. In my view, it is a dangerous existence when one lives without it. But now the fundamental question we have to ask is: &amp;ldquo;What is indeed data analysis anyway?&amp;rdquo;</description></item><item><title>Dirty Data: Why Cleaning Takes Longer Than Analysis</title><link>https://magazine.thetextsmith.com/data-analysis/dirty-data-why-cleaning-takes-longer-than-analysis/</link><pubDate>Sat, 01 Aug 2026 07:10:20 +0200</pubDate><guid>https://magazine.thetextsmith.com/data-analysis/dirty-data-why-cleaning-takes-longer-than-analysis/</guid><description>It is a universal truth that textsmiths work with data formats. Yet formats are attempts to impose structure on messy reality, but no format can decide what the right structure is for you. So in this article, we are going to look at what data cleaning is.</description></item></channel></rss>