{"id":7329,"date":"2017-05-02T07:00:51","date_gmt":"2017-05-02T15:00:51","guid":{"rendered":"http:\/\/formtek.com\/blog\/?p=7329"},"modified":"2017-03-28T08:08:56","modified_gmt":"2017-03-28T16:08:56","slug":"big-data-businesses-find-big-data-success-stories-possible-but-hard-to-replicate","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/big-data-businesses-find-big-data-success-stories-possible-but-hard-to-replicate\/","title":{"rendered":"Big Data: Businesses Find Big Data Success Stories Possible, but Hard to Replicate"},"content":{"rendered":"<p>Big Data has made big promises, and that has been a problem. \u00a0While Big Data has had<a href=\"https:\/\/datafloq.com\/read\/12-amazing-big-data-success-stories-for-2016\/1770\"> many successes<\/a>, many companies trying to achieve similar successes have struggled. \u00a0Using technologies like Big Data and Analytics is\u00a0getting easier, but still, being\u00a0successful with big data often takes a skillset that many companies have not yet grown or recruited.<\/p>\n<p><a href=\"http:\/\/scholar.harvard.edu\/len\/home\">Leonard D\u2019Avolio<\/a>, assistant professor at Harvard Medical School and CEO of health IT vendor Cyft, <a href=\"http:\/\/www.healthcareitnews.com\/news\/frustrated-big-data-harvard-professor-says-its-justified\">said that<\/a> &#8220;the excitement and anticipation of the potential of Big Data technologies and approaches is probably equally matched by the ambiguity, confusion and hype surrounding what these technologies are.\u00a0What we learned from that, after the necessary growing pains of wasting billions of dollars trying to jam what is in effect new ways of doing business into existing companies without a very exact focus on the problem you are trying to solve and careful consideration of the existing constraints and workflows, is that you are very likely to end up basically running around with a hammer assuming every problem is a nail.\u201d<\/p>\n<p>For some time Big Data was synonymous with Hadoop. \u00a0More recently newer technologies like Apache Spark have improved usability, but it&#8217;s still not easy. Many of the newer Big Data technologies still are built around or have dependencies on Hadoop. Hadoop has benefits, but it is also complex and has comparatively slow performance.<\/p>\n<p><a href=\"https:\/\/en.wikipedia.org\/wiki\/Bob_Muglia\">Bob Muglia<\/a>, CEO of Snowflake Computing,\u00a0<a href=\"https:\/\/www.datanami.com\/2017\/03\/13\/hadoop-failed-us-tech-experts-say\/\">told Datanami<\/a> that &#8220;I can\u2019t find a happy Hadoop customer. It\u2019s sort of as simple as that. It\u2019s very clear to me, technologically, that it\u2019s not the technology base the world will be built on going forward. The number of customers who have actually successfully tamed Hadoop is probably less than 20, and it might be less than 10. That\u2019s just nuts given how long that product, that technology has been in the market and how much general industry energy has gone into it.&#8221;<\/p>\n<p><a href=\"https:\/\/www.interana.com\/who-we-are\/team\/\">Bobby Johnson<\/a>,\u00a0co-founder of Interana, <a href=\"https:\/\/www.datanami.com\/2017\/03\/13\/hadoop-failed-us-tech-experts-say\/\">said of Hadoop that<\/a> &#8220;there\u2019s a bunch of things that people have been trying to do with it for a long time that it\u2019s just not well suited for.\u00a0It\u2019s never really broken out of the developer world. People have this idea of, \u2018Oh there\u2019s all these legacy data warehouses and the new cool way to do it is Hadoop.\u2019 But when you try to do that, you realize it\u2019s actually a lot worse. 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