<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Timothée Poisot on The Carpentries</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/author/timoth%C3%A9e-poisot/</link><description>Recent content in Timothée Poisot on The Carpentries</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 20 Nov 2024 10:51:28 -0500</lastBuildDate><atom:link href="https://deploy-preview-705--carpentries-website.netlify.app/blog/author/timoth%C3%A9e-poisot/index.xml" rel="self" type="application/rss+xml"/><item><title>The SQL Ecology Lessons</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/2017/01/whyweteach-sql/</link><pubDate>Mon, 23 Jan 2017 00:00:00 +0000</pubDate><guid>https://deploy-preview-705--carpentries-website.netlify.app/blog/2017/01/whyweteach-sql/</guid><description>&lt;p>&lt;strong>This post originally appeared on the &lt;a href="https://datacarpentry.org">Data Carpentry website&lt;/a>&lt;/strong>&lt;/p>
&lt;p>I am fond of saying that ecologists should not be afraid of big data &amp;ndash;
instead, we have to deal with small, complex, and poorly connected data.
Understanding how we can stay on top of things, data-wise, is becoming
more and more important. And some of the practices used to collect a small
amount of data do not scale well at all when the amount of data increases,
even if slightly.&lt;/p></description></item></channel></rss>