Customer and business analytics : applied data mining for business decision making using R /
By: Putler, Daniel S
Title By: Krider, Robert E
Material type:![](/opac-tmpl/lib/famfamfam/BK.png)
Item type | Home library | Call number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|
REGULAR | University of Wollongong in Dubai Main Collection | 658.40302855133 PU CU (Browse shelf) | Available | T0010886 |
Includes bibliographical references and index.
Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics algorithms work. Where necessary, the authors explain the underlying mathematics in an accessible manner. Each technique presented includes a detailed tutorial that enables hands-on experience with real data. The authors also discuss issues often encountered in applied data mining projects and present the CRISP-DM process model as a practical framework for organizing these projects. Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities.