Understanding the Predictive Analytics Life Cycle

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3 Understanding the Predictive Analytics Life Cycle

4 Wiley & SAS Business Series The Wiley & SAS Business Series presents books that help senior-level managers with their critical management decisions. Titles in the Wiley & SAS Business Series include: Analytics in a Big Data World: The Essential Guide to Data Science and its Applications by Bart Baesens Bank Fraud: Using Technology to Combat Losses by Revathi Subramanian Big Data Analytics: Turning Big Data into Big Money by Frank Ohlhorst Big Data, Big Innovation: Enabling Competitive Differentiation through Business Analytics by Evan Stubbs Business Analytics for Customer Intelligence by Gert Laursen Business Intelligence Applied: Implementing an Effective Information and Communications Technology Infrastructure by Michael Gendron Business Intelligence and the Cloud: Strategic Implementation Guide by Michael S. Gendron Business Transformation: A Roadmap for Maximizing Organizational Insights by Aiman Zeid Connecting Organizational Silos: Taking Knowledge Flow Management to the Next Level with Social Media by Frank Leistner Delivering Business Analytics: Practical Guidelines for Best Practice by Evan Stubbs Demand-Driven Forecasting: A Structured Approach to Forecasting, Second Edition by Charles Chase Demand-Driven Inventory Optimization and Replenishment: Creating a More Efficient Supply Chain by Robert A. Davis

5 Developing Human Capital: Using Analytics to Plan and Optimize Your Learning and Development Investments by Gene Pease, Barbara Beresford, and Lew Walker The Executive s Guide to Enterprise Social Media Strategy: How Social Networks Are Radically Transforming Your Business by David Thomas and Mike Barlow Economic and Business Forecasting: Analyzing and Interpreting Econometric Results by John Silvia, Azhar Iqbal, Kaylyn Swankoski, Sarah Watt, and Sam Bullard Foreign Currency Financial Reporting from Euros to Yen to Yuan: A Guide to Fundamental Concepts and Practical Applications by Robert Rowan Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data Driven Models by Keith Holdaway Health Analytics: Gaining the Insights to Transform Health Care by Jason Burke Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World by Carlos Andre Reis Pinheiro and Fiona McNeill Human Capital Analytics: How to Harness the Potential of Your Organization s Greatest Asset by Gene Pease, Boyce Byerly, and Jac Fitz-enz Implement, Improve, and Expand Your Statewide Longitudinal Data System: Creating a Culture of Data in Education by Jamie McQuiggan and Armistead Sapp Killer Analytics: Top 20 Metrics Missing from Your Balance Sheet by Mark Brown Predictive Analytics for Human Resources by Jac Fitz-enz and John Mattox II Predictive Business Analytics: Forward-Looking Capabilities to Improve Business Performance by Lawrence Maisel and Gary Cokins Retail Analytics: The Secret Weapon by Emmett Cox Social Network Analysis in Telecommunications by Carlos Andre Reis Pinheiro Statistical Thinking: Improving Business Performance, Second Edition by Roger W. Hoerl and Ronald D. Snee

6 Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics by Bill Franks Too Big to Ignore: The Business Case for Big Data by Phil Simon Using Big Data Analytics: Turning Big Data into Big Money by Jared Dean The Value of Business Analytics: Identifying the Path to Profitability by Evan Stubbs The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions by Phil Simon Win with Advanced Business Analytics: Creating Business Value from Your Data by Jean Paul Isson and Jesse Harriott For more information on any of the above titles, please visit

7 Understanding the Predictive Analytics Life Cycle Alberto Cordoba

8 Cover image: istock.com/oliopi Cover design: Wiley Copyright 2014 by Alberto Cordoba. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) , fax (978) , or on the Web at Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) , fax (201) , or online at Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) , outside the United States at (317) or fax (317) Wiley publishes in a variety of print and electronic formats and by print-ondemand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at For more information about Wiley products, visit Library of Congress Cataloging-in-Publication Data: ISBN (Hardcover) ISBN (epdf) ISBN (epub) Printed in the United States of America

9 Dedicated to my loving family

10

11 Contents Foreword Preface xiii xi Acknowledgments xv Chapter 1 Problem Identification and Definition 1 Importance of Clear Business Objectives 4 Office Politics 8 Note 13 Chapter 2 Design and Build 15 Managing Phase 16 Planning Phase 18 Delivery Phase 19 Notes 32 Chapter 3 Data Acquisition 33 Data: The Fuel for Analytics 36 A Data Scientist s Job 41 Notes 53 Chapter 4 Exploration and Reporting 55 Visualization 57 Cloud Reporting 61 Chapter 5 Modeling 69 Churn Model 71 Risk Scoring Model 77 Notes 99 Chapter 6 Actionable Analytics 101 Digital Asset Management 104 Social Media 104 ix

12 x CONTENTS Chapter 7 Feedback 129 What the Different Software Components Should Do 132 Note 148 Conclusion 149 Appendix: Useful Questions 155 Bibliography 209 About the Author 211 Index 213

13 Foreword With this book, Al has made an astonishing contribution to the growing body of knowledge about business analytics. The book offers an unprecedented look into the gory details of life as a programmer/ analyst, BI specialist, researcher, project manager, data scientist, and consultant. It offers examples of problem solving that could only have been applied by using the progressive power of information technologies that was mastered in the 1990s and 2000s. Have there been other books about this topic? Of course, but none has portrayed the human side of this global endeavor with so much enthusiasm and humor before. For the first time, Al personifies the characters that play important roles in the lifecycle of the generation and use of predictive analytics, showing their creative abilities in industries such as banking, megaresorts, mobile operators, healthcare, manufacturing, and retail. These personifications helps us all better understand and manage this big and complex process of deriving information from data in today s increasingly sophisticated race to drive productivity and innovation. This understanding is essential to excel at providing an outstanding customer experience, manage customer churn, and perform dataintensive marketing campaigns. This book has many novelistic aspects and is very conversational. This way the stories do make each section more personal and relatable. The Note Files in particular will be quite helpful for readers as they present examples of real-life analytics projects. These files can be used as good starting seeds for projects. Leigh Watts xi

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15 Preface People get excited about big data and business analytics. That might sound ridiculous, but I m not kidding. Over the years, I have traveled everywhere from Brazil to Japan working on analytics, and in every country, I have found a particularly peculiar brand of analytic fanaticism. These analysts are hilarious and downright exciting! I wrote this book to help business and IT professionals understand the predictive analytics lifecycle. A reader can get a sense for the entire predictive cycle and therefore avoid potential risks. Often folks who work in a particular area of the analytics cycle for example, analysis have little understanding of another area, such as integration. This situation sometimes creates confusions, poor communication, and delays. This book has seven chapters, which illustrate a complete cycle from idea definition to feedback. In each chapter, I added notes at the end with examples. The first chapter concentrates on the initial stages of defining the problem at hand and how to get the business customer to quantify the overall business value of the project. The note file contains a sample nondisclosure agreement. Chapter 2, the design chapter, focuses on the planning process. It shows how to define various components of the scope, such as what organizations are affected, what to expect, and the type of information required. The note file has a sample project for a data warehouse performance management project. Chapter 3, the integration chapter, discusses the process of bringing data together to build a file ready for analysis. This chapter includes two notes: One is a data-quality sample project, and the other is a file with a description of Hadoop and how it works with SAS. Chapter 4, the reporting and visualization chapter, illustrates how reporting and visualization techniques are used to review and make sense of data. The chapter includes a note file with an example of an analytic project focused on xiii

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