The purpose of this book is to outline a diverse range of commonly used approaches to making and communicating decisions from data, using data visualization, clustering, and predictive analytics. The book relates these topics to how they can be used in practice in a variety of ways. First, the methods outlined in the book are discussed within the context of a data mining process that starts with defining the problem and ends with deployment of the results. Second, each method is outlined in detail, including a discussion of when and how they should be used. Third, examples are provided throughout to further illustrate how the methods operate. Fourth, there is a detailed discussion of applications in which these approaches are being applied today. Finally, software called Traceis™, which can be used with the examples in the book or with data sets of interest to the reader, is available for downloading from a companion website.

The book is aimed towards professionals in any discipline who are interested in making decisions from data in addition to understanding how data mining can be used. Undergraduate and graduate students taking courses in data mining through a Bachelors, Masters, or MBA program could use the book as a resource. The approaches have been outlined to an extent that software professionals could use the book to gain insight into the principles of data visualization and advanced data mining algorithms in order to help in the development of new software products. ...

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