{"id":4560,"date":"2014-12-17T14:05:46","date_gmt":"2014-12-17T14:05:46","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=4560"},"modified":"2014-12-17T14:05:46","modified_gmt":"2014-12-17T14:05:46","slug":"solve-engineering-data-dilemma","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/solve-engineering-data-dilemma\/4560\/","title":{"rendered":"Solve the Engineering Data Dilemma"},"content":{"rendered":"Big Data has been both hailed as the currency of the Information Age and derided as overhyped. Both statements are true because data immediately loses much of its value if it cannot be properly analyzed and acted upon to help make decisions. Making use of data is getting more difficult as the amount of product information that needs to be shared explodes with increasingly complex products. At last month\u2019s NIWeek in Austin, TX, National Instruments\u2019 Executive Vice President of Global Sales and Marketing Eric Starkloff shared some sobering facts on our ability to generate data during a keynote <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/solve-engineering-data-dilemma\/4560\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Big Data has been both hailed as the currency of the Information Age and derided as overhyped. Both statements are true because data immediately loses much of its value if it cannot be properly analyzed and acted upon to help make decisions. Making use of data is getting more difficult as the amount of product [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11,48],"tags":[84,384,385],"class_list":["post-4560","post","type-post","status-publish","format-standard","hentry","category-industry-news","category-left-hand","tag-cloud-computing","tag-commentary","tag-data-management"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/4560","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=4560"}],"version-history":[{"count":2,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/4560\/revisions"}],"predecessor-version":[{"id":4562,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/4560\/revisions\/4562"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=4560"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=4560"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=4560"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}