{"id":1349,"date":"2010-07-08T07:00:02","date_gmt":"2010-07-08T15:00:02","guid":{"rendered":"http:\/\/www.formtek.com\/blog\/?p=1349"},"modified":"2010-07-08T07:00:02","modified_gmt":"2010-07-08T15:00:02","slug":"data-a-future-made-for-data-scientists","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/data-a-future-made-for-data-scientists\/","title":{"rendered":"Data:  A Future Made For Data Scientists"},"content":{"rendered":"<p>Tim O&#8217;Reilly <a title=\"Data is the new Intel Inside\" href=\"http:\/\/dld.bz\/fHTT\" target=\"_blank\">commented years<\/a> ago that &#8220;Data is the new Intel Inside&#8221;. \u00a0Data is transforming the way many companies do business, and for some companies like Google, without data they would have no business. \u00a0Research groups like <a title=\"Data Doubling every 18 months\" href=\"http:\/\/www.tgdaily.com\/hardware-features\/42499-digital-content-doubles-every-18-months\" target=\"_blank\">IDC and Gartner<\/a> estimate the volume of data growth parallels <a title=\"Moore's Laws\" href=\"http:\/\/en.wikipedia.org\/wiki\/Moore's_law\" target=\"_blank\">Moore&#8217;s law<\/a> and is doubling every eighteen months.<\/p>\n<p>In a posting on O&#8217;Reilly by <a href=\"http:\/\/radar.oreilly.com\/mikel\">Mike Loukides<\/a>, he argues that a new job category called the\u00a0<a title=\"Data Scientist definition\" href=\"http:\/\/tamingdata.com\/2010\/01\/18\/roger-magoulas-defines-a-data-scientist\/\" target=\"_blank\">Data Scientist<\/a> is emerging to help interpret and find meaning from from this massive of data that everyone is collecting. \u00a0Data Scientists are well versed in statistics, but they&#8217;re more than just statisticians. \u00a0They&#8217;re renaissance people that have strong analytic skills drawn from a number of areas. \u00a0<a title=\"Nathan Yau on the Data Scientist\" href=\"http:\/\/flowingdata.com\/2009\/06\/04\/rise-of-the-data-scientist\/\" target=\"_blank\">Nathan Yau<\/a> characterized the Data Scientist as someone with strong skills from all of these areas:<\/p>\n<div id=\"_mcePaste\">\n<ul>\n<li><strong>Computer Science<\/strong> &#8211; acquire and parse data<\/li>\n<li><strong>Mathematics, Statistics, &amp; Data Mining<\/strong> &#8211; filter and mine<\/li>\n<li><strong>Graphic Design<\/strong> &#8211; represent and refine<\/li>\n<li><strong>Infovis (Information Visualization) and Human-Computer Interaction (HCI) <\/strong>&#8211; interaction<\/li>\n<\/ul>\n<\/div>\n<p>Loukides similarly summarizes Data Scientists as follows:<\/p>\n<blockquote><p>Data scientists combine entrepreneurship with patience, the willingness to build data products incrementally, the ability to explore, and the ability to iterate over a solution. They are inherently interdiscplinary. They can tackle all aspects of a problem, from initial data collection and data conditioning to drawing conclusions. They can think outside the box to come up with new ways to view the problem, or to work with very broadly defined problems: &#8220;here&#8217;s a lot of data, what can you make from it?&#8221;<\/p><\/blockquote>\n<p><a title=\"Ben Lorika on Data Scientist\" href=\"http:\/\/radar.oreilly.com\/2010\/04\/big-data-tool-for-business-analysts.html\" target=\"_blank\">Ben Lorika<\/a> noted that Data Scientist is a title that has been picked up and used by cutting-edge tech companies like\u00a0Yahoo!, Facebook, Linkedin, Twitter, the <a title=\"New York Times Data Scientist Job\" href=\"http:\/\/twitter.com\/bigdata\/status\/11679520858\" target=\"_blank\">New York Times<\/a>. \u00a0 So, Data Scientists are already here today and and it&#8217;s likely we will only see more of them in the future.<\/p>\n<div class=\"lightsocial_container\"><div class=\"lightsocial_element\"><a class=\"lightsocial_a\" 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