Data Mining for Business Analytics ― Concepts, Techniques, and Applications in Xlminer

Incorporating an innovative focus on data visualization and time series forecasting,Data Mining for Business Intelligence, Third Edition continues to supply insightful, detailed guidance on fundamental data mining techniques. This new edition guides readers through the use of the Microsoft Office ExcelR add-in XLMinerR (now in a student version) for developing predictive models and techniques in order to describe and find patterns in data. The authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods. The book includes free access to the student edition of XLMinerR, allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Each chapter concludes with exercises that allow readers to expand their comprehension of the presented material. Over a dozen cases that require use of the different data mining techniques are introduced, and a related Web site features over two dozen data sets, exercise solutions, PowerPoint slides, and case solutions. New to this edition are topics including text analytics, recommender systems, social network analysis, getting data from a database into the analytics process, and scoring and employing the results of an analysis to a database.