A Practical Guide to Data Mining for Business and Industry: Case Studies and Methodology - Hardcover

Ahlemeyer-Stubbe, Andrea; Coleman, Shirley

 
9781119977131: A Practical Guide to Data Mining for Business and Industry: Case Studies and Methodology

Synopsis

Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.

"synopsis" may belong to another edition of this title.

About the Author

Andrea Ahlemeyer-Stubbe, Director Strategic Analytics, DRAFTFCB München GmbH, Germany

Shirley Coleman, Principal Statistician, Industrial Statistics Research Unit, School of Maths and Statistics, Newcastle University, UK

From the Back Cover

A Practical Guide to Data Mining for Business and Industry

A Practical Guide to Data Mining for Business and Industry presents a user friendly approach to data mining methods and provides a solid foundation for their application. The methodology presented is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. This book is designed so that the reader can cross-reference a particular application or method to sectors of interest. The necessary basic knowledge of data mining methods is also presented, along with sector issues relating to data mining and its various applications.

A Practical Guide to Data Mining for Business and Industry:

  • Equips readers with a solid foundation to both data mining and its applications
  • Provides tried and tested guidance in finding workable solutions to typical business problems
  • Offers solution patterns for common business problems that can be adapted by the reader to their particular areas of interest
  • Focuses on practical solutions whilst providing grounding in statistical practice
  • Explores data mining in a sales and marketing context, as well as quality management and medicine
  • Is supported by a supplementary website (www.wiley.com/go/data_mining) featuring datasets and solutions

Aimed at statisticians, computer scientists and economists involved in data mining as well as students studying economics, business administration and international marketing.

From the Inside Flap

A Practical Guide to Data Mining for Business and Industry

A Practical Guide to Data Mining for Business and Industry presents a user friendly approach to data mining methods and provides a solid foundation for their application. The methodology presented is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. This book is designed so that the reader can cross-reference a particular application or method to sectors of interest. The necessary basic knowledge of data mining methods is also presented, along with sector issues relating to data mining and its various applications.

A Practical Guide to Data Mining for Business and Industry:

  • Equips readers with a solid foundation to both data mining and its applications
  • Provides tried and tested guidance in finding workable solutions to typical business problems
  • Offers solution patterns for common business problems that can be adapted by the reader to their particular areas of interest
  • Focuses on practical solutions whilst providing grounding in statistical practice
  • Explores data mining in a sales and marketing context, as well as quality management and medicine
  • Is supported by a supplementary website (www.wiley.com/go/data_mining) featuring datasets and solutions

Aimed at statisticians, computer scientists and economists involved in data mining as well as students studying economics, business administration and international marketing.

"About this title" may belong to another edition of this title.