Data is changing the way businesses and other organizations work. Back in the day, the challenge was getting data; now the challenge is making sense of it, sifting through the noise to find the signal, and providing actionable insights to decision-makers. Those of us who work with data, especially on the frontend—statisticians, data scientists, business analysts, and the like—have many programming languages from which to choose.
R is a go-to programming language with an ever-expanding upside for slicing and dicing large data sets, conducting statistical tests of significance, developing predictive models, producing unsupervised learning algorithms, and creating top-quality visual content. Beginners and professionals alike, up and down an organization and across multiple verticals, rely on the power of R to generate insights that drive purposeful action.