Data and Text Mining : A Business Applications Approach

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This conceptual introduction to data mining within the context of business and marketing research provides a uniquely balanced approach that is neither too technical nor too management oriented. Using worked examples and business case studies, the text answers these 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? An excellent primer for upper-level courses in Business, Computer Science and Statistics. Features Accessible introductory approach—To the statistical procedures and computer algorithms involved in data mining. Provides students with a non-technical introduction to the field with minimal technical. Real business case study based. Provides students with real business data. Provides instructors with data-based cases for classroom demonstrations and class assignments. Balanced view of the role of data mining in business and marketing research—i.e. Compares modern, data-adaptive methods with traditional methods, reviewing the advantages and disadvantages of both. Relevance of data mining. Shows students how data mining can provide useful information to business and marketing managers. Concise yet complete. Provides students with just the right amount of information to supply an adequate management introduction without overwhelming them by details. First book to include “Text Mining” topic. Shows students how and why of text data organization and extraction. Table Of Contents 1. What Is Data Mining? 2. Traditional Methods of Data Mining. 3. Data-Adaptive Methods. 4. Text Mining. 5. And In Conclusion.