<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data Visualization on DataAgentX</title><link>https://e343c64b.dataagentx.pages.dev/en/tags/data-visualization/</link><description>Recent content in Data Visualization on DataAgentX</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Wed, 14 Oct 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://e343c64b.dataagentx.pages.dev/en/tags/data-visualization/index.xml" rel="self" type="application/rss+xml"/><item><title>Reproducible Calculations Make Charts Credible</title><link>https://e343c64b.dataagentx.pages.dev/en/tech/20261014-reproducible-analysis/</link><pubDate>Wed, 14 Oct 2026 00:00:00 +0000</pubDate><guid>https://e343c64b.dataagentx.pages.dev/en/tech/20261014-reproducible-analysis/</guid><description>&lt;p&gt;&lt;a href="https://e343c64b.dataagentx.pages.dev/images/articles/reproducible-analysis/core-en.svg"&gt;&lt;img src="https://e343c64b.dataagentx.pages.dev/images/articles/reproducible-analysis/core-en.svg" alt="A reproducible analysis workspace connecting notebooks and charts"&gt;&lt;/a&gt;&lt;/p&gt;&#10;&lt;p&gt;The same chart changes when someone else reruns the analysis. The same data tells a different story when the axis changes. Details like these often undermine a Data Agent&amp;rsquo;s credibility.&lt;/p&gt;&#10;&lt;p&gt;Data Analytics Skills divides this work between two Skills: &lt;code&gt;Jupyter Notebooks&lt;/code&gt; makes the calculations reproducible, while &lt;code&gt;Visualize Data&lt;/code&gt; keeps their presentation from misleading readers. The first explains where a number comes from; the second establishes what a chart can support.&lt;/p&gt;</description></item><item><title>When Is a Data Agent Report Actually Delivered?</title><link>https://e343c64b.dataagentx.pages.dev/en/tech/20260913-delivery-and-action-loop/</link><pubDate>Sun, 13 Sep 2026 00:00:00 +0000</pubDate><guid>https://e343c64b.dataagentx.pages.dev/en/tech/20260913-delivery-and-action-loop/</guid><description>&lt;p&gt;An agent has generated a report on declining new-customer conversion. The task is not finished. A business leader needs to know whether the conclusion supports a decision, an analyst needs to recompute material values, and an operations team may need an investigation ticket. They require different artifacts and may have different data rights.&lt;/p&gt;&#10;&lt;p&gt;Delivery is complete when an authorized recipient can understand, verify, and use the result. Recommendation, approval, submission, confirmed effect, and business impact must remain separate states.&lt;/p&gt;</description></item></channel></rss>