{"id":2833,"date":"2013-12-20T20:45:53","date_gmt":"2013-12-20T20:45:53","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=2833"},"modified":"2013-12-20T20:46:05","modified_gmt":"2013-12-20T20:46:05","slug":"perfect-information-doesnt-equal-perfect-predictions","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/perfect-information-doesnt-equal-perfect-predictions\/2833\/","title":{"rendered":"Perfect Information Doesn&#8217;t Equal Perfect Predictions"},"content":{"rendered":"Many organizations attempt to achieve \u201cdata nirvana\u201d by having 100% complete information for any given business decision. In the customer analytics space, this is sometimes referred to as a \u201c360 degree view of the customer.\u201d However, we really never know everything about our customers. What we call a 360 degree view is really just the most complete view we have at any given time. All of the information we are missing must be inferred or assumed through analytics. The more complete our picture, the less we have to infer, but realistically we are usually inferring far more information <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/perfect-information-doesnt-equal-perfect-predictions\/2833\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Many organizations attempt to achieve \u201cdata nirvana\u201d by having 100% complete information for any given business decision. In the customer analytics space, this is sometimes referred to as a \u201c360 degree view of the customer.\u201d However, we really never know everything about our customers. What we call a 360 degree view is really just the [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11],"tags":[125,262,263,8],"class_list":["post-2833","post","type-post","status-publish","format-standard","hentry","category-industry-news","tag-business-intelligence","tag-market-research","tag-modeling","tag-predictive-analytics"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2833","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=2833"}],"version-history":[{"count":2,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2833\/revisions"}],"predecessor-version":[{"id":2835,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2833\/revisions\/2835"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=2833"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=2833"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=2833"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}