The updated 5th edition of the book Data Mining for Business Analytics from Galit Shmueli and collaborators and published by Wiley is a standard guide to data mining and analytics that adds two new co-authors and a trove of new material vis-á-vis its predecessor. R is a free, open-source and popularity-gaining software environment for statistical computing and graphics. Trailing with the subtitle Concepts, Techniques, and Applications in R, the new 5th edition of Data Mining for Business Analytics continues to provide an applied approach to data-mining concepts and methods, using the R software as a canvas on which to illustrate.

With the book, readers learn how to implement a variety of popular data-mining algorithms in R to tackle business problems and opportunities. Material covered in-depth includes both statistical and machine-learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis.

The new 5th edition includes material from business, government, a dozen case studies demonstrating applications for the data-mining techniques described, and exercises in each chapter that help readers gauge and expand their comprehension and competency of the material. Data Mining for Business Analytics can serve as either a text book or a reference for analysts, researchers and practitioners working with quantitative methods in myriad fields.