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Companies face big challenges with big data analytics applications
Sponsored by SearchBusinessAnalytics
It's hardly breaking news, but businesses today are looking to cash in on big data. And naturally, vendors of big data analytics applications are trying to capitalize on that by promising new opportunities for companies looking to increase revenues and gain competitive advantages over business rivals. What you won't hear about, at least not as readily, are the challenges they first need to overcome.
In this three-part guide, three consultants weigh in with concrete offers of encouragement for companies struggling to turn big data -- large, varied and fast-changing data sets -- into valuable business insight. First, Wayne Eckerson serves up an in-depth analysis of Hadoop. The open source software offers companies a platform for reining in the spreadmarts set up by data analysts and business users, while still giving them a place to do self-service analytics. Next, Keith B. Carter delivers a warning about big mistakes that many organizations make on big data analytics projects, with tips on how to avoid them. Barry Devlin, the founder and principal of 9sight Consulting, finishes with a cautionary note about overreliance on data analytics at the expense of intuitive decision making.
Table Of Contents
- Hadoop offers single spot for spreadmarts, analytics
- Two big mistakes put big data projects in peril
- Don’t let data oust intuition in decision making
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