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(More customer reviews)This book got its start as notes for a data mining class that one of us (Nitin Patel) was teaching at MIT, and was completed while another of us (Galit Shmueli) was teaching a similar course at Maryland. Both courses were part of an MBA program. We found that, while there are a lot of books on data mining, there were none that actually gave business students the skills and tools to implement data mining algorithms. So we set ourselves the task of writing a book that (1) provides real data sets with a business decision-making context and a hands-on orientation , (2) provides a theoretical and practical understanding of the key data mining methods of classification, prediction, data reduction and exploration at a level that is appropriate and useful for MBA's, and (3) bundles a powerful version of a commercial data mining tool that works in Excel (XLMiner). For this reason, we think our book will be appropriate not just for students, but also for business analysts with a quantitative orientation, on, indeed, anyone who wants to learn data mining via self-study. Have we succeeded? You be the judge!- P. Bruce (for G. Shmueli and N. Patel)
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Data Mining for Business Intelligence, Second Edition uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models. Featuring complimentary access to XLMiner®, the Microsoft Office Excel® add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of DM techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples, now doubled in number in the second edition, are provided to motivate learning and understanding. This book helps readers understand the beneficial relationship that can be established between DM and smart business practices, and is an excellent learning tool for creating valuable strategies and making wiser business decisions. New topics include detailed coverage of visualization (enhanced by Spotfire subroutines) and time series forecasting, among a host of other subject matter.
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