R is an open source, interpreted programming language designed specifically for statistical data analysis. A recent surge in popularity has resulted in it becoming the most widely used programming language in data science. It has become essential in providing analytics driven solutions in fields such as finance, online marketing, geopolitics, and consumer protection. R’s large user base has produced an extensive library of community reviewed “packages”, resulting in highly extensible functionality that facilitates the creation of virtually every data manipulation, statistical, and predictive modelling tool needed in a Business Intelligence environment.
As a programming language rather than a boxed software, R allows for the custom creation and reuse of solutions to complex challenges. It offers support for a wide variety of statistical and graphical techniques including linear and non-linear modeling, classical statistical tests and time-series analysis. As the open source code is mostly written in C and Fortran, programmers can use these languages to control R objects directly. This provides the capacity to engineer highly complex, and highly flexible data driven solutions.
According to Revolution Analytics (the commercial manifestation of R ), R has “more than 2 million global users.” Its versatility and power are leveraged by companies such as Google, Facebook, Linked In, Bank of America, Ford, Kickstarter, and Twitter, as well as federal organizations like the FDA, National Weather Service, and the EPA. Custom chart and data visualizations created with R can be seen in the New York Times, the Economist and New Scientist magazine
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