Book description
“This book is a splendid and valuable addition to this subject. The whole book is well written and I have no hesitation to recommend that this can be adapted as a textbook for graduate courses in Business Intelligence and Data Mining.” Dr. Edi Shivaji, Des Moines, Iowa “As a complete novice to this area just starting out on a MBA course I found the book incredibly useful and very easy to follow and understand. The concepts are clearly explained and make it an easy task to gain an understanding of the subject matter.” -- Mr. Craig Domoney, South Africa. Business Intelligence and Data Mining is a conversational and informative book in the exploding area of Business Analytics. Using this book, one can easily gain the intuition about the area, along with a solid toolset of major data mining techniques and platforms. This book can thus be gainfully used as a textbook for a college course. It is also short and accessible enough for a busy executive to become a quasi-expert in this area in a couple of hours. Every chapter begins with a case-let from the real world, and ends with a case study that runs across the chapters.
Table of contents
- Cover
- Half Title Page
- Title Page
- Copyright
- Dedication
- Abstract
- Contents
- Preface
- Chapter 1 Wholeness of Business Intelligence and Data Mining
-
Section 1
- Chapter 2 Business Intelligence Concepts and Applications
- Chapter 3 Data Warehousing
-
Chapter 4 Data Mining
- Gathering and Selecting Data
- Data Cleansing and Preparation
- Outputs of Data Mining
- Evaluating Data Mining Results
- Data Mining Techniques
- Tools and Platforms for Data Mining
- Data Mining Best Practices
- Myths about Data Mining
- Data Mining Mistakes
- Conclusion
- Review Questions
- Liberty Stores Case Exercise: Step 3
-
Section 2
- Chapter 5 Decision Trees
- Chapter 6 Regression
- Chapter 7 Artificial Neural Networks
-
Chapter 8 Cluster Analysis
- Applications of Cluster Analysis
- Definition of a Cluster
- Representing Clusters
- Clustering Techniques
- Clustering Exercise
- K-Means Algorithm for Clustering
- Selecting the Number of Clusters
- Advantages and Disadvantages of K-Means Algorithm
- Conclusion
- Review Exercises
- Liberty Stores Case Exercise: Step 6
- Chapter 9 Association Rule Mining
- Section 3
- Additional Resources
- Index
Product information
- Title: Business Intelligence and Data Mining
- Author(s):
- Release date: December 2014
- Publisher(s): Business Expert Press
- ISBN: 9781631571213
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