Real-World Data Mining: Applied Business Analytics and Decision Making

Overview

Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance.

Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques ...

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Overview

Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance.

Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials.

Real-World Data Mining will be valuable to professionals on analytics teams; professionals seeking certification in the field; and undergraduate or graduate students in any analytics program: concentrations, certificate-based, or degree-based.

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Product Details

  • ISBN-13: 9780133551075
  • Publisher: Pearson FT Press
  • Publication date: 1/6/2015
  • Series: FT Press Analytics Series
  • Edition number: 1
  • Pages: 240

Meet the Author

DR. DURSUN DELEN (Tulsa, OK) is William S. Spears and Neal Patterson Chair in Business Analytics, Director of Research for the Center for Health Systems Innovation, and Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University. As research scientist at Knowledge Based Systems Inc., he led advanced decision support, information systems and analytics research projects funded by DoD, NASA, NIST and DOE. His research has appeared in Decision Support Systems, Communications of the ACM, Computers and Operations Research, Computers in Industry, Journal of Production Operations Management, Artificial Intelligence in Medicine, Expert Systems with Applications, and other leading journals. His books include Advanced Data Mining Techniques; Decision Support and Business Intelligence Systems; Business Intelligence: A Managerial Approach; and Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications. He co-chaired the 4th International Conference on Network Computing and Advanced Information Management, is associate editor-in-chief for International Journal of Experimental Algorithms, and is associate editor for International Journal of RF Technologies and Journal of Decision Analytics.

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Table of Contents

1. An Overview of Business Analytics and Data Mining

2. An Introduction to Data Mining

3. Data Mining Process

4. Data in Data Mining

5. Data Mining Methods

6. Data Mining Techniques

7. Performance Evaluation

8. Data Mining Tools

9. An Overview of Text Mining

10. An Overview of Web Mining

11. An Overview of Sentiment Analysis

12. Big Data and Data Mining

Modern data mining made easy: all the concepts, techniques, and case studies you need to use data mining for evidence-based decision-making.

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