<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Organizational on Ryan Orban</title><link>https://ryanorban.com/categories/organizational/</link><description>Recent content in Organizational on Ryan Orban</description><generator>Hugo</generator><language>en-us</language><managingEditor>me@ryanorban.com (Ryan Orban)</managingEditor><webMaster>me@ryanorban.com (Ryan Orban)</webMaster><copyright>Ryan Orban</copyright><lastBuildDate>Sun, 17 Mar 2013 00:00:00 +0000</lastBuildDate><atom:link href="https://ryanorban.com/categories/organizational/index.xml" rel="self" type="application/rss+xml"/><item><title>The Utilization Gap: Big Data's Biggest Challenge</title><link>https://ryanorban.com/notes/big-data-utilization-gap/</link><pubDate>Sun, 17 Mar 2013 00:00:00 +0000</pubDate><author>me@ryanorban.com (Ryan Orban)</author><guid>https://ryanorban.com/notes/big-data-utilization-gap/</guid><description>&lt;p&gt;&lt;img
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&lt;p&gt;By 2013, the big data narrative had shifted from &amp;ldquo;how do we store and process this data? to a harder question: why aren&amp;rsquo;t we actually using it?&amp;rdquo; The Forbes piece identified what it called the utilization gap — the space between the data organizations were collecting and the decisions that data was actually informing. Most enterprises had invested in Hadoop clusters, data warehouses, and ETL pipelines, but the analysts and decision-makers who needed to act on the data were still working from gut feeling and spreadsheets.&lt;/p&gt;</description></item></channel></rss>