<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Survey on Harlan D. Harris</title><link>https://harlanh.tech/tags/survey/</link><description>Recent content in Survey on Harlan D. Harris</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>harlan@harris.name (Harlan Harris)</managingEditor><webMaster>harlan@harris.name (Harlan Harris)</webMaster><lastBuildDate>Tue, 23 Oct 2012 00:00:00 +0000</lastBuildDate><atom:link href="https://harlanh.tech/tags/survey/index.xml" rel="self" type="application/rss+xml"/><item><title>Communication and the Data Scientist</title><link>https://harlanh.tech/2012/10/communication-and-the-data-scientist/</link><pubDate>Tue, 23 Oct 2012 00:00:00 +0000</pubDate><author>harlan@harris.name (Harlan Harris)</author><guid>https://harlanh.tech/2012/10/communication-and-the-data-scientist/</guid><description>
&lt;p&gt;I recently gave a presentation on communication issues around the terms “Data Science” and “Data Scientist”, based in part on a survey that I did with my Meetup colleagues Marck and Sean. The basic idea is that these new, extremely-broad buzzwords have resulted in confusion, which has impacted the ability of people with skills and people with data to meet and effectively communicate about who does what and what appropriate expectations should be. The survey was an attempt to bring some clarity to the issue of who are the people in this newly-reformulated community, and how do they view themselves and their skills. For more on the survey, see &lt;a href="http://datacommunitydc.org/blog/2012/08/data-scientists-survey-results-teaser/" target="_blank"&gt;our post on the Data Community DC blog&lt;/a&gt;. Here’s the video of my presentation at &lt;a href="http://datagotham.com" target="_blank"&gt;DataGotham&lt;/a&gt;:&lt;/p&gt;</description></item><item><title>Survey of Data Science / Analytics / Big Data / Applied Stats / Machine Learning etc. Practitioners</title><link>https://harlanh.tech/2012/05/survey-of-data-science-analytics-big-data-applied-stats-machine-learning-etc-practitioners/</link><pubDate>Thu, 10 May 2012 00:00:00 +0000</pubDate><author>harlan@harris.name (Harlan Harris)</author><guid>https://harlanh.tech/2012/05/survey-of-data-science-analytics-big-data-applied-stats-machine-learning-etc-practitioners/</guid><description>
&lt;p&gt;&lt;a title="Data Science, Moore’s Law, and Moneyball" href="https://harlanh.tech/2011/09/data-science-moores-law-and-moneyball/" target="_blank" rel="noopener"&gt;As I’ve discussed here before&lt;/a&gt;, there is a debate raging (ok, maybe not raging) about terms such as “data science”, “analytics”, “data mining”, and “big data”. What do they mean, how do they overlap, and perhaps most importantly, who are the people who work in these fields?&lt;/p&gt;
&lt;p&gt;Along with two other DC-area Data Scientists, Marck Vaisman and Sean Murphy, I’ve put together a survey to explore some of these issues. Help us quantitatively understand the space of data-related skills and careers by participating!&lt;/p&gt;</description></item></channel></rss>