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  • Video how-to: Speed up R with C++ and Rcpp

    Sometimes when using R, you'll want more speed than base R can offer. That's why some advanced R users combine R and C++ -- and there's a package that makes it easy for you do so, too.

    Written by By Jared Lander07 Aug. 15 23:36
  • 8 ways to make the most out of your customer data

    Everyone talks about the importance of big data. But many organizations, although they collect and store customer data, do not put that data to good use -- or they don't know how to.

    Written by Jennifer Lonoff Schiff16 June 15 04:20
  • Big Data ROI Will Take Time, Clear Goals and Talent

    The big data market is expected, by one estimate, to grow more than 30 percent annually until the end of the decade. But more than half of big data projects fail--and even those that do succeed can fall apart if the findings aren't applied to operational efficiencies. Ron Bodkin, CEO of Think Big Analytics, offers advice to help you prevent your business from becoming just another statistic.

    Written by Brian Eastwood22 July 13 14:45
  • 6 Big Data Analytics Use Cases for Healthcare IT

    Making use of the petabytes of patient data that healthcare organizations possess requires extracting it from legacy systems, normalizing it and then building applications that can make sense of it. That's a tall order, but the facilities that pull it off can learn a lot.

    Written by Brian Eastwood23 April 13 13:20
  • 6 CIOs Share Their Strategic Visions for 2013

    If your IT organization doesn't have a clear core strategy, it's easy to get caught up in--and spend too much on--technology trends. Learn about six CIOs' strategies for 2013 and see how they compare to your plans for the rest of the year.

    Written by John Brandon30 Jan. 13 14:38
  • Big Data, Cheap Storage Bring In-Memory Analytics Into Spotlight

    In-memory analytics, like virtualization and the cloud, is an old idea that's been given new life. In this case, the combination of big data, inexpensive commodity storage and parallel processing make it possible to analyze terabytes of data without slowing systems to a crawl.

    Written by Allen Bernard06 Dec. 12 14:05
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