<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data-Governance on Gabriel Berardi</title><link>http://www.gabriel-berardi.com/tags/data-governance/</link><description>Recent content in Data-Governance on Gabriel Berardi</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Sat, 14 Sep 2024 00:00:00 +0000</lastBuildDate><atom:link href="http://www.gabriel-berardi.com/tags/data-governance/index.xml" rel="self" type="application/rss+xml"/><item><title>Simple Questions, Hard Answers</title><link>http://www.gabriel-berardi.com/blog/data/2024-09-30-simple-questions-hard-answers/</link><pubDate>Sat, 14 Sep 2024 00:00:00 +0000</pubDate><guid>http://www.gabriel-berardi.com/blog/data/2024-09-30-simple-questions-hard-answers/</guid><description>&lt;p&gt;When business stakeholders ask data experts seemingly simple questions, they often expect a quick and straightforward answer. On the surface, it seems like a piece of cake. But in the messy reality of data, what appears to be a simple question can quickly turn into a multi-layered onion of a problem - each layer revealing increasing complexity and ambiguity.&lt;/p&gt;
&lt;p&gt;Let&amp;rsquo;s take a practical example from the insurance industry. A sales executive asks:&lt;/p&gt;</description></item></channel></rss>