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.
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.
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.
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.
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.
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.
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.