Big Data and Business Analytics Mark Ferguson, Editor Business Intelligence and Data Mining Anil K. Maheshwari, Ph.D. Business Intelligence and Data Mining Business Intelligence and Data Mining Anil K. Maheshwari, PhD Business Intelligence and Data Mining Copyright © Anil K. Maheshwari, PhD, 2015. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations, not to exceed 400 words, without the prior permission of the publisher. First published by Business Expert Press, LLC 222 East 46th Street, New York, NY 10017 www.businessexpertpress.com ISBN-13: 978-1-63157-120-6 (print) ISBN-13: 978-1-63157-121-3 (e-book) eISSN: 2333-6757 ISSN: 2333-6749 Business Expert Press Big Data and Business Analytics Collection. Cover and interior design by S4Carlisle Publishing Services Private Ltd., Chennai, India Dedicated to my parents, Mr. Ratan Lal and Mrs. Meena Maheshwari. Abstract Business is the act of doing something productive to serve someone’s needs, and thus earn a living, and make the world a better place. Business activities are recorded on paper or using electronic media, and then these records become data. There is more data from customers’ responses and on the industry as a whole. All this data can be analyzed and mined using special tools and techniques to generate patterns and intelligence, which reflect how the business is functioning. These ideas can then be fed back into the business so that it can evolve to become more effective and ef- ficient in serving customer needs. And the cycle continues on. Business intelligence includes tools and techniques for data gather- ing, analysis, and visualization for helping with executive decision making in any industry. Data mining includes statistical and machine-learning techniques to build decision-making models from raw data. Data mining techniques covered in this book include decision trees, regression, artifi- cial neural networks, cluster analysis, and many more. Text mining, web mining, and big data are also covered in an easy way. A primer on data modeling is included for those uninitiated in this topic. Keywords Data Analytics, Data Mining, Business Intelligence, Decision Trees, Regression, Neural Networks, Cluster analysis, Association rules. Contents 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