Data Mining for Business Intelligence  (English, Paperback, Shmueli Galit)

Data Mining For Business Intelligence, provides practical and comprehensive guidance in all the fundamental techniques of data mining to its users, practitioners and students.

Summary Of The Book

Data Mining For Business Intelligence provides a detailed study of all the aspects of Data mining, illustrating, with the help of real examples, how these methods can be used effectively and positively in Business.

The first Chapter introduces the reader to the vast field of Data Mining. Beginning with the basic question of ‘What is Data Mining?’, the book covers its origins, use, growth, various methods and terminologies. Going deeper with core ideas and steps in Data Mining, it goes on to give a complete and comprehensive study of the topic. The second Chapter, Overview of the Data Mining Process deals with topics like Core Ideas in Data Mining, Steps in Data Mining and Use of Excel in Data Mining. The third chapter is Data Exploration and Dimension Reduction. Chapter 5 is Multiple Linear Regression and chapter 6 is Three simple Classification Methods. These are followed by the chapters Classification and Regression Trees, Logistic Regression, Neural Nets, Discriminant Analysis, Association Rules and Cluster Analysis.

The writers use real-world, interesting examples to enable readers to theoretically and practically understand important methods of data mining. At the end of each chapter are exercises which help the reader to gauge his understanding of the topic. Perhaps the best feature of the book is its use of the Microsoft Office Excel add-in, XLMiner, to make illustration and interpretation easier for the user. It also makes practical work easily accessible.

The intention of the book was to make a comprehensive, detailed study about Data Mining available to students and practitioners, using an easy to understand, case-oriented method. Data Mining For Business Intelligence helps the readers see the connection between the intelligent application of data mining and success in business.

About the Authors

Galit Shmueli is an Assistant Professor, and Researcher

She has also co- authored the books Modeling Online Auctions and Statistical Methods in e-Commerce Research.

She received her Phd from Israel Institute of Technology in the year 2000. Currently the Professor of Statistics and Information Systems at the Indian School of Business, Hyderabad, she has also worked as a Director of The eMarkets Research Lab and Associate Professor Of Statistics. She has several journal articles and textbooks to her credit. She holds several workshops and conducts many courses online. Shmueli has taught in institutes, taken government and corporate courses in several countries including India, United States, and Israel.

Nitin Patel, Chairman and co-founder of Massachusetts based Cytel, Inc, served for almost 10 years at Massachusetts Institute of Technology, as a visiting Professor.

An expert in the field of Computer Algorithms and Statistics, he has more than 65 published papers to his credit. He was also a Professor at IIM, Ahmedabad and a visiting Professor at Harvard, University of Michigan, University of Montreal, and University of Pittsburgh. In 1987, Dr. Patel was the joint recipient of the George W. Snedecor Award from the American Statistical Association.

Peter. C. Bruce is the Owner and President of one of the leading providers of online education in the field of Statistics, statistics.com.