{"id":2783,"date":"2013-12-10T18:38:22","date_gmt":"2013-12-10T18:38:22","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=2783"},"modified":"2013-12-10T18:38:22","modified_gmt":"2013-12-10T18:38:22","slug":"analytics-3-0-the-old-guard-masters-how-to-build-data-products","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/analytics-3-0-the-old-guard-masters-how-to-build-data-products\/2783\/","title":{"rendered":"Analytics 3.0 &#8212; the old guard masters how to build data products"},"content":{"rendered":"Asked to name a big data company, many of us would say Google or Facebook or eBay. But for old-school giants such as General Electric Co. and Macy&#8217;s Inc., big data is fast becoming as central to their business models as jet engines and women&#8217;s apparel.That&#8217;s the conclusion Tom Davenport, president&#8217;s chair and distinguished professor of information technology and management at Babson College and co-founder of International Institute for Analytics, came to after he and Jill Dych\u00e9, vice president of best practices for SAS Institute Inc., looked at what happened when 20 traditional companies adopted big data. &#8220;Many <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/analytics-3-0-the-old-guard-masters-how-to-build-data-products\/2783\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Asked to name a big data company, many of us would say Google or Facebook or eBay. But for old-school giants such as General Electric Co. and Macy&#8217;s Inc., big data is fast becoming as central to their business models as jet engines and women&#8217;s apparel.That&#8217;s the conclusion Tom Davenport, president&#8217;s chair and distinguished professor [&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":[251,250,252,249,246,166,253,248,247],"class_list":["post-2783","post","type-post","status-publish","format-standard","hentry","category-industry-news","tag-academic-analytics","tag-big-data-as-a-service-bdaas","tag-chief-experience-officer-cxo","tag-data-latency","tag-data-management-platform-dmp","tag-data-science","tag-enterprise-it-enterprise-class-it","tag-microtargeting","tag-prescriptive-analytics"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2783","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=2783"}],"version-history":[{"count":2,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2783\/revisions"}],"predecessor-version":[{"id":2785,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2783\/revisions\/2785"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=2783"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=2783"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=2783"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}