{"id":8563,"date":"2013-08-11T23:22:05","date_gmt":"2013-08-11T23:22:05","guid":{"rendered":"http:\/\/www.cloudcomputing-news.net\/news\/2013\/aug\/12\/how-big-data-improves-and-complicates-predictive-analytics\/"},"modified":"2013-08-11T23:22:05","modified_gmt":"2013-08-11T23:22:05","slug":"how-big-data-improves-and-complicates-predictive-analytics","status":"publish","type":"post","link":"https:\/\/icloud.pe\/blog\/how-big-data-improves-and-complicates-predictive-analytics\/","title":{"rendered":"How big data improves &#8211; and complicates &#8211; predictive analytics"},"content":{"rendered":"<p><strong>By Andy Flint, FICO<\/strong><\/p>\n<p>Analytics depends on data &mdash; the more, the merrier. If we&rsquo;re trying to model, say, the behaviour of customers responding to marketing offers or clicking through a website, we can build a far stronger model with 10,000 samples than with 100.<\/p>\n<p>You would think, then, that the rise of Big Data and its seemingly inexhaustible supply of data would be every analyst&rsquo;s dream. But Big Data poses its own challenges for modelling. Much of Big Data isn&rsquo;t what we have historically thought of as &ldquo;data&rdquo; at all. In fact, 80% of Big Data is raw, unstructured information, such as text, and doesn&rsquo;t neatly fit into the columns and rows that feed most modelling programs.<\/p>\n<p>Here&rsquo;s how data scientists seeking to harness Big Data for predictive modelling have addressed the challenges presented by a mass of messy data.<\/p>\n<h3>Turning words into numbers &#8230;<\/h3>\n","protected":false},"excerpt":{"rendered":"<p>By Andy Flint, FICO<br \/>\nAnalytics depends on data &mdash; the more, the merrier. If we&rsquo;re trying to model, say, the behaviour of customers responding to marketing offers or clicking through a website, we can build a far stronger model with 10,000 sam&#8230;<\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-8563","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/8563","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/comments?post=8563"}],"version-history":[{"count":0,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/8563\/revisions"}],"wp:attachment":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/media?parent=8563"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/categories?post=8563"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/tags?post=8563"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}