The confluence of three major trends: the unprecedented growth of the mobile web, the acceptance of cloud computing as a viable model for business applications and the demand for sophisticated predictive analytics is driving demand for web applications that are backed by advanced analytical techniques and data visualizations that are well beyond the simple, canned analyses that characterized early business intelligence efforts. For example, an application to provide near real-time, web-accessible customer risk profiles to department managers located throughout an enterprise is not far-fetched in today’s environment. Developing such an application might require evaluating and then deploying classification algorithms only recently published in the statistical journals. The R language is particularly well suited for this fast moving quantitative world. R is interpretative language that is ideal for the rapid prototyping of new techniques. Furthermore, R can package these techniques in a very small profile. R scripts containing only code required for particular calculations fit nicely into the web applications development environments.
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