{"id":5648,"date":"2013-03-15T12:56:11","date_gmt":"2013-03-15T19:56:11","guid":{"rendered":"http:\/\/www.blackswanreport.com\/blog\/?p=5648"},"modified":"2013-03-15T12:56:11","modified_gmt":"2013-03-15T19:56:11","slug":"big-data-caveats-front-and-center-information-management-blogs-article","status":"publish","type":"post","link":"https:\/\/www.blackswanreport.com\/blog\/2013\/03\/big-data-caveats-front-and-center-information-management-blogs-article\/","title":{"rendered":"Big Data Caveats, Front and Center &#8211; Information Management Blogs Article"},"content":{"rendered":"<blockquote>\n<p>Given that backdrop, Taleb\u2019s misgivings on big data and analytics aren\u2019t at all surprising: \u201cWe\u2019re more fooled by noise than ever before, and it\u2019s because of a nasty phenomenon called \u201cbig data.\u201d With big data, researchers have brought cherry-picking to an industrial level \u2026 Modernity provides too many variables, but too little data per variable. So the spurious relationships grow much, much faster than real information \u2026 In other words: Big data may mean more information, but it also means more false information \u2026 In observational studies, statistical relationships are examined on the researcher\u2019s computer. In double-blind cohort experiments, however, information is extracted in a way that mimics real life \u2026 This is not all bad news though: If such studies cannot be used to confirm, they can be effectively used to debunk \u2014 to tell us what\u2019s wrong with a theory, not whether a theory is right.\u201d<\/p>\n<\/blockquote>\n<p>via <a href=\"http:\/\/www.information-management.com\/blogs\/big-data-caveats-front-and-center-10024081-1.html\">Big Data Caveats, Front and Center &#8211; Information Management Blogs Article<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Given that backdrop, Taleb\u2019s misgivings on big data and analytics aren\u2019t at all surprising: \u201cWe\u2019re more fooled by noise than ever before, and it\u2019s because of a nasty phenomenon called \u201cbig data.\u201d With big data, researchers have brought cherry-picking to an industrial level \u2026 Modernity provides too many variables, but too little data per variable. [&hellip;]<\/p>\n","protected":false},"author":8,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[530],"tags":[680],"class_list":["post-5648","post","type-post","status-publish","format-standard","hentry","category-antifragility-2","tag-big-data"],"_links":{"self":[{"href":"https:\/\/www.blackswanreport.com\/blog\/wp-json\/wp\/v2\/posts\/5648","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.blackswanreport.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.blackswanreport.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.blackswanreport.com\/blog\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/www.blackswanreport.com\/blog\/wp-json\/wp\/v2\/comments?post=5648"}],"version-history":[{"count":0,"href":"https:\/\/www.blackswanreport.com\/blog\/wp-json\/wp\/v2\/posts\/5648\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.blackswanreport.com\/blog\/wp-json\/wp\/v2\/media?parent=5648"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.blackswanreport.com\/blog\/wp-json\/wp\/v2\/categories?post=5648"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.blackswanreport.com\/blog\/wp-json\/wp\/v2\/tags?post=5648"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}