{"id":6155,"date":"2015-08-30T10:00:31","date_gmt":"2015-08-30T14:00:31","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=6155"},"modified":"2015-08-27T10:37:58","modified_gmt":"2015-08-27T14:37:58","slug":"big-data-analytics-software-options0829151","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/big-data-analytics-software-options0829151\/6155\/","title":{"rendered":"Big Data Analytics Software Options"},"content":{"rendered":"There are many vendors selling products classified as big data analytics software. However, it&#8217;s challenging to differentiate these products based on functionality alone, as many of the tools share similar features and capabilities. Additionally, some of the tools exhibit extremely subtle differences. \u00a0That being said, your key differentiating factors will likely focus on balancing ease of use, algorithmic sophistication and price in relation to your organization&#8217;s capability and level of maturity in analytics. In this article, we examine products from nine big data analytics software vendors: Alteryx, IBM, KNIME.com, Microsoft, Oracle, RapidMiner, SAP, SAS and Teradata. Some of <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/big-data-analytics-software-options0829151\/6155\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>There are many vendors selling products classified as big data analytics software. However, it&#8217;s challenging to differentiate these products based on functionality alone, as many of the tools share similar features and capabilities. Additionally, some of the tools exhibit extremely subtle differences. \u00a0That being said, your key differentiating factors will likely focus on balancing ease [&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":[42],"class_list":["post-6155","post","type-post","status-publish","format-standard","hentry","category-industry-news","tag-big-data"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/6155","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=6155"}],"version-history":[{"count":1,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/6155\/revisions"}],"predecessor-version":[{"id":6156,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/6155\/revisions\/6156"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=6155"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=6155"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=6155"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}