"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.

Maharishi University of Management

Abstract ..................................................................................................v Preface ................................................................................................xiii Chapter 1 Wholeness of Business Intelligence and Data Mining ........1 Business Intelligence .........................................................2 Pattern Recognition ..........................................................3 Data Processing Chain ......................................................6 Organization of the Book ................................................16 Review Questions ............................................................17 Section 1 ..................................................................................... 19 Chapter 2 Business Intelligence Concepts and Applications .............21 BI for Better Decisions ....................................................23 Decision Types ................................................................23 BI Tools ..........................................................................24 BI Skills ..........................................................................26 BI Applications ..............................................................26 Conclusion......................................................................34 Review Questions ............................................................35 Liberty Stores Case Exercise: Step 1 .................................35 Chapter 3 Data Warehousing ...........................................................37 Design Considerations for DW .......................................38 DW Development Approaches ........................................39 DW Architecture ............................................................40 Data Sources ...................................................................40 Data Loading Processes ...................................................41 DW Design .....................................................................41 DW Access ......................................................................42 DW Best Practices ...........................................................43 Conclusion......................................................................43 Review Questions ............................................................43 Liberty Stores Case Exercise: Step 2 .................................44 Chapter 4 Data Mining ..................................................................45 Gathering and Selecting Data ..........................................47 Data Cleansing and Preparation ......................................48 Outputs of Data Mining .................................................49 Evaluating Data Mining Results ......................................50 Data Mining Techniques .................................................51 Tools and Platforms for Data Mining ..............................54 Data Mining Best Practices .............................................56 Myths about Data Mining ..............................................57 Data Mining Mistakes .....................................................58 Conclusion......................................................................59 Review Questions ............................................................60 Liberty Stores Case Exercise: Step 3 .................................60 Section 2 ..................................................................................... 61 Chapter 5 Decision Trees .................................................................63 Decision Tree Problem ....................................................64 Decision Tree Construction ............................................66 Lessons from Constructing Trees .....................................71 Decision Tree Algorithms ................................................72 Conclusion......................................................................75 Review Questions ...........................................................75 Liberty Stores Case Exercise: Step 4 .................................76 Chapter 6 Regression .......................................................................77 Correlations and Relationships ........................................78 Visual Look at Relationships ...........................................79 Regression Exercise..........................................................80 Nonlinear Regression Exercise .........................................83 Logistic Regression ..........................................................85 Advantages and Disadvantages of Regression Models .....86 Conclusion......................................................................88 Review Exercises ..............................................................88 Liberty Stores Case Exercise: Step 5 .................................89 Chapter 7 Artificial Neural Networks ..............................................91 Business Applications of ANN ........................................92 Design Principles of an ANN ..........................................93 Representation of a Neural Network ..............................95 Architecting a Neural Network .......................................95 Developing an ANN .......................................................96 Advantages and Disadvantages of Using ANNs ...............97 Conclusion......................................................................98 Review Exercises ..............................................................98 Chapter 8 Cluster Analysis ..............................................................99 Applications of Cluster Analysis ....................................100 Definition of a Cluster ..................................................101 Representing Clusters ....................................................102 Clustering Techniques ...................................................102 Clustering Exercise ........................................................103 K-Means Algorithm for Clustering ................................106 Selecting the Number of Clusters .................................109 Advantages and Disadvantages of K-Means Algorithm ..................................................................110 Conclusion....................................................................111 Review Exercises ............................................................111 Liberty Stores Case Exercise: Step 6 ...............................112 Chapter 9 Association Rule Mining ..............................................113 Business Applications of Association Rules ...................114 Representin…