{"id":12300,"date":"2013-02-24T00:37:56","date_gmt":"2013-02-23T23:37:56","guid":{"rendered":"http:\/\/timoelliott.com\/blog\/?p=4693"},"modified":"2013-02-24T00:37:56","modified_gmt":"2013-02-23T23:37:56","slug":"gartnerbi-and-big-data-fear-loathing-and-business-breakthroughs","status":"publish","type":"post","link":"https:\/\/timoelliott.com\/blog\/2013\/02\/gartnerbi-and-big-data-fear-loathing-and-business-breakthroughs.html","title":{"rendered":"#GartnerBI and Big Data: Fear, Loathing, and Business Breakthroughs"},"content":{"rendered":"

\"big<\/p>\n

At the Gartner Business Intelligence and Analytics Summit in Barcelona, there was near universal agreement about three things to do with \u201cbig data\u201d<\/p>\n

    \n
  1. It\u2019s an awful term (but we\u2019re stuck with it)<\/li>\n
  2. Whatever it means, it\u2019s a big deal, and requires big changes to traditional information infrastructures<\/li>\n
  3. It will result in big new business opportunities<\/li>\n<\/ol>\n

    \u201cBig Data\u201d is a terrible term<\/h3>\n

    Gartner analyst\u00a0Doug Laney<\/a>\u00a0first coined the term \u201cbig data\u201d over over 12 years ago<\/a> (at least in its current form \u2013 people have been complaining about \u201cinformation overload\u201d since Roman times). But the term\u2019s meaning is still far from clear and it was nominated the #1 \u201ctech buzzword<\/a> that everyone uses but don\u2019t quite understand\u201d (followed closely by \u201ccloud\u201d).<\/p>\n

    When using the term, Gartner usually keeps the quote marks in place (i.e. it\u2019s \u201cbig data\u201d, not big data). Here\u2019s the definition provided by analyst Ted Friedman<\/a> to \u201cde-hype\u201d the term during the summit keynote:<\/p>\n

    “Big Data” are high volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision-making\u201d<\/p><\/blockquote>\n

    Analyst Donald Feinberg<\/a> warned people that \u201ctalking only about big data can lead to self-delusion\u201d and urged people not to \u201csurrender to the hype-ocracy.\u201d He left left no doubt over where he stood on the use of the term: \u201cBig data doesn\u2019t mean MapReduce or Hadoop. Big data doesn\u2019t exist, it\u2019s meaningless, it\u2019s ridiculous\u2026\u201d The audience started applauding, to which he replied: \u201cWhy are you clapping?! Why do you all fall for it? Why do the vendors do it?!<\/p>\n

    As SAP\u2019s Jason Rose?<\/a> put it \u201chow can we demystify this? …easy, drop the \u2018big\u2019. Data has always been the key challenge in BI\u201d.<\/p>\n

    For what it\u2019s worth, here\u2019s my tongue-in-cheek definition<\/a>, and it\u2019s worth noting that big data is quickly becoming the default term<\/a> for what we used to call analytics or business intelligence.<\/p>\n

    But Big Data is a Big Deal<\/h3>\n

    Despite the problems, Doug Laney noted that big data the most-searched-for term on Gartner.com.\u00a0 Why is it so popular? Maybe because it\u2019s so nebulous that people want to check if they have understood it. Or maybe because there\u2019s no other more precise term to indicate the new analytic opportunities. And maybe because \u201chype has a value\u201d as Ted Friedman<\/a> put it: big data has proved to be a new opportunity to talk to business people about the power of analytics, and because everybody\u2019s searching for it, vendors would be crazy not to include it in their marketing.<\/p>\n

    Conference attendees generally believed that the biggest opportunity for big data analysis was new insights from \u201cdark data\u201d that lies unused within organizations today. Gartner highlighted the dangers of implementing shiny new big data technology, separate from existing analytics infrastructures: \u201cDo not make your big data implementations siloed. Make them part of the overall strategy for BI.\u201d said<\/a> Ted Friedman. \u201cLink to stuff you are already doing. Don\u2019t make big data a standalone thing. And don\u2019t feel like you\u2019ve got to go out and buy a whole new technology stack.\u201d<\/p>\n

    Analyst Rita Sallam<\/a>, in a session on data variety, gave some examples of the new opportunities:<\/p>\n

    \"\"<\/p>\n

    Some of Gartner\u2019s public predictions<\/a> related to big data:<\/p>\n