A unique Open Source programming language known simply as “R” is becoming increasingly popular based on its ease of use and ability to analyze massive data sets. The GNU-based computer programming language is similar in some ways to S Statistical Programming language, but with key elements making it particularly helpful in crunching large sets of numbers.

R programming language was developed by two programmers at the University of Aukland in the early 1990′s, and has become a favorite tool for statistical analysis on a large scale. Currently, over two million users are taking advantage of R, particularly scientists, programmers and academics who routinely do research.

Speed is one of the biggest draws for R programming language, which can process up to 12 gigabytes of data in seconds. Among the useful applications in R are linear and nonlinear modeling, time series analysis, classifications, clustering, and classic statistical tests. It can run on UNIX, MacOS, and Windows. Its popularity is in part due to ability to produce top quality plots using various mathematical symbols, a boon to anyone seeking to publish results.

Although two million users is a relatively small number on the global scale, there are several indications that this Open Source programming language is going to move on to bigger and better things. Power hitters like Oracle and IBM are now offering limited support for R programming language, and a few small businesses have actually invested in offering software based on R.

Recently, the business intelligence sector began taking notice of the many benefits of R programming language, which is particularly adaptive to predictive analytics. It can be to identify patterns or trends in massive data sets, making it ideal for research into retail, financial, and medical trends. Wal-Mart is a high profile user of R, using it to interpret the needs and spending habits of customers. With so much interest, it seems clear that R programming language will continue to grow in popularity.