Data and Text Mining : A Business Applications Approach

Thomas W. Miller

ISBN 10: 0131400851 / ISBN 13: 9780131400856

Published by Pearson, 2004

About this Item

[ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: first ] Publisher: Prentice Hall Pub Date: 4/6/2004 Binding: Paperback Pages: 192 first edition.

Seller Inventory # 6690963

Bibliographic Details

• Title: Data and Text Mining : A Business Applications Approach
• Publisher: Pearson
• Publication Date: 2004
• Language: English
• ISBN 10: 0131400851
• ISBN 13: 9780131400856
• Binding: Soft cover
• Condition: Good

About this title

Synopsis

This conceptual introduction to data mining within the context of business and marketing research provides an eclectic approach to the field. Using worked examples and business case studies, the volume answers the four questions: why is data mining important to business and marketing research; how is data mining different from other types of research; what do we learn from data mining; and how do we do data mining? The book explains data mining, traditional methods, data-adaptive methods and applications in business and marketing with business cases and provides lists of tables, figures and exhibits. For Managers and Analysts.

From the Back Cover

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To learn how a company can grow their business by harnessing more information, you need Data and Text Mining.

Inside this book you will find a manager's introduction to Data and Text Mining. The emphasis is on business data, including information about firms and markets, products and prices, supplier actions and buyer responses. By focusing on business applications such as customer relationship management, database marketing, market segmentation, sales forecasting, and more, you'll be shown just, how Data and Text Mining results can be used to guide business decision making.

Written in a non-technical, non-mathematical style, this book is an excellent tool for any course where learning to make decisions based on real data is important!