Wholeness of data analytics --
Business intelligence concepts and application --
Data warehousing --
Data mining --
Data visualization --
Decision trees --
Regression --
Artificial neural networks --
Cluster analysis --
Association rule mining --
Text mining --
Naïve-Bayes analysis --
Support vector machines --
Web mining --
Social network analysis --
Big data --
Data modeling primer --
Statistics primer --
Data science careers and additional case studies --
Appendix 1: R tutorial for data mining --
Appendix 2: Weka tutorial for data mining --
Additional resources --
Index.

"This is a concise and conversational textbook in the growing field of Data Analytics. Easy to read and informative, this lucid book covers important concepts with concrete examples, and invites the reader to join this field. This book is designed to provide a learner with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms. Learners across variety of academic discplines, including business, computer science, statistics, engineering, and others attracted to the idea of discovering new insights and ideas from data will enjoy this book. The chapters in the book are organized for a typical one-semester course"--Back cover