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R was designed 20 years ago to allow academic statisticians and others with sophisticated programming skills to perform complex data statistical analysis and display the results in any of a multitude of visual graphics. In the past, R has been criticized for delivering slow analyses when applied to large data sets, but more recent versions of the language are attempting to address this problem.
Today, R is being adopted by enterprise users for big data analytics and is increasingly being seen as a challenger to more traditional statistical and advanced analytic platforms. Some vendors now support the use of R in their software or offer completely R-based packages. This means that instead of having to write complex R code, today's users can create sophisticated data models simply by using a front-end graphical user interface (GUI) and pointing and clicking. At the time of this writing, Oracle , SAS and TIBCO have incorporated R support into some of their products and Revolution Analytics is offering an R-based environment.
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