Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner: A Beginner's Guide

183 Pages·2014·3.05 MB·English

Business Analytics Using
SAS® Enterprise Guide® and

SAS® Enterprise Miner™
A Beginner’s Guide
Olivia Parr-Rud
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The correct bibliographic citation for this manual is as follows: Parr-Rud, Olivia. 2014. Business Analytics Using SAS®
Enterprise Guide® and SAS® Enterprise Miner®: A Beginner’s Guide. Cary, NC: SAS Institute Inc.
Business Analytics Using SAS® Enterprise Guide® and SAS® Enterprise Miner®: A Beginner’s Guide
Copyright © 2014, SAS Institute Inc., Cary, NC, USA
ISBN 978-1-62959-327-2
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Contents

About This Book ...................................................................................... vii
About the Author ...................................................................................... xi
Chapter 1: Defining the Business Objective ............................................... 1
Introduction .................................................................................................................................... 1
Setting Goals .................................................................................................................................. 1
Descriptive Analyses ...................................................................................................................... 3
Customer Profile ...................................................................................................................... 3
Customer Loyalty ..................................................................................................................... 4
Market Penetration or Wallet Share ...................................................................................... 4
Predictive Analyses ........................................................................................................................ 4
Marketing Models .................................................................................................................... 5
Risk and Approval Models ...................................................................................................... 6
Predictive Modeling Opportunities by Industry .................................................................... 9
Notes from the Field .................................................................................................................... 13
Chapter 2: Data Types, Categories, and Sources ..................................... 15
Introduction .................................................................................................................................. 15
The Evolution of Data................................................................................................................... 16
Types of Data ................................................................................................................................ 17
Nominal Data .......................................................................................................................... 17
Ordinal Data ........................................................................................................................... 17
Continuous Data .................................................................................................................... 18
Categories of Data ....................................................................................................................... 18
Demographic or Firmographic Data .................................................................................... 18
Behavioral Data ...................................................................................................................... 19
Psychographic Data .............................................................................................................. 20
iv Contents
Data Category Comparison .................................................................................................. 20
Sources of Data ............................................................................................................................ 21
Internal Sources ..................................................................................................................... 21
Storage of Data ...................................................................................................................... 27
External Sources .................................................................................................................... 28
Notes from the Field .................................................................................................................... 29
Chapter 3: Overview of Descriptive and Predictive Analyses .................... 29
Introduction .................................................................................................................................. 29
Descriptive Analyses .................................................................................................................... 30
Frequency Distributions ........................................................................................................ 30
Cluster ..................................................................................................................................... 33
Decision Tree ......................................................................................................................... 33
Predictive Analyses ...................................................................................................................... 35
Linear Regression .................................................................................................................. 36
Logistic Regression ............................................................................................................... 39
Neural Networks .................................................................................................................... 41
Modeling Process ........................................................................................................................ 43
Define the Objective .............................................................................................................. 43
Develop the Model ................................................................................................................. 43
Implement the Model ............................................................................................................ 48
Maintain the Model ................................................................................................................ 49
Notes from the Field .................................................................................................................... 52
Chapter 4: Data Construction for Analysis ............................................... 53
Introduction .................................................................................................................................. 53
Data for Descriptive Analysis ...................................................................................................... 53
Data for Predictive Analysis ........................................................................................................ 54
Prospect Models .................................................................................................................... 55
Customer Models .................................................................................................................. 57
Risk Models ............................................................................................................................ 59
External Sources of Data ............................................................................................................. 61
Notes from the Field .................................................................................................................... 61
Chapter 5: Descriptive Analysis Using SAS Enterprise Guide ................... 63
Introduction .................................................................................................................................. 63
Project Overview .......................................................................................................................... 63
Contents v

Project Initiation ........................................................................................................................... 64
Exploratory Analysis .................................................................................................................... 65
Importing the Data ................................................................................................................. 65
Viewing the Data .................................................................................................................... 66
Exploring the Data ................................................................................................................. 66
Segmentation and Profile Analysis............................................................................................. 69
Correlation Analysis ..................................................................................................................... 76
Notes from the Field .................................................................................................................... 77
Chapter 6: Market Analysis Using SAS Enterprise Guide .......................... 79
Introduction .................................................................................................................................. 79
Project Overview .......................................................................................................................... 79
Market Analysis ............................................................................................................................ 80
Project Initiation ..................................................................................................................... 80
Data Preparation .................................................................................................................... 80
Penetration and Share of Wallet .......................................................................................... 89
Results .................................................................................................................................... 90
Notes from the Field .................................................................................................................... 91
Chapter 7: Cluster Analysis Using SAS Enterprise Miner .......................... 93
Introduction .................................................................................................................................. 93
Project Overview .......................................................................................................................... 93
Cluster Analysis ............................................................................................................................ 94
Initiate the Project ................................................................................................................. 94
Input the Data Source and Assign Variable Roles ............................................................. 97
Transform Variables .............................................................................................................. 99
Filter Data ............................................................................................................................. 102
Build Clusters ....................................................................................................................... 104
Build Segment Profiles ........................................................................................................ 107
Analyze Clusters and Recommend Marketing or Product Development Actions ........ 109
Notes from the Field .................................................................................................................. 109
Chapter 8: Tree Analysis Using SAS Enterprise Miner ............................ 111
Introduction ................................................................................................................................ 111
Project Overview ........................................................................................................................ 111
Decision Tree Analysis .............................................................................................................. 112
Initiate the Project ............................................................................................................... 112
vi Contents
Input the Data Source ......................................................................................................... 114
Create Target Variable ........................................................................................................ 115
Partition the Data ................................................................................................................. 117
Build the Decision Tree ....................................................................................................... 118
View the Decision Tree Output ........................................................................................... 120
Interpret the Findings .......................................................................................................... 126
Alternate Uses for Tree Analysis ........................................................................................ 128
Notes from the Field .................................................................................................................. 128
Chapter 9: Predictive Analysis Using SAS Enterprise Miner ................... 129
Introduction ................................................................................................................................ 129
Select ........................................................................................................................................... 130
Initiate the Project ............................................................................................................... 130
Select the Data ..................................................................................................................... 131
Explore ........................................................................................................................................ 133
StatExplore ........................................................................................................................... 133
MultiPlot ................................................................................................................................ 136
Modify .......................................................................................................................................... 138
Replace Missing Values via Imputation ............................................................................. 138
Partition Data into Subsamples ......................................................................................... 139
Manage Outliers ................................................................................................................... 140
Transform the Variables ...................................................................................................... 142
Model ........................................................................................................................................... 145
Decision Tree ....................................................................................................................... 145
Neural Network .................................................................................................................... 147
Regression ........................................................................................................................... 148
Assess ......................................................................................................................................... 151
Notes from the Field .................................................................................................................. 155
References ............................................................................................ 157
About This Book
Purpose
This book serves as a tutorial for data analysts who are new to SAS Enterprise Guide and SAS
Enterprise Miner. It provides valuable hands-on experience using powerful statistical software to
complete the kinds of business analytics common to most industries. With clear, illustrated, step-
by-step instructions, it will lead you through examples based on business case studies. You will
formulate the business objective, manage the data, and perform analyses that you can use to
optimize marketing, risk, and customer relationship management, as well as business processes and
human resources.
Prerequisites
If you are a savvy business person with a desire to understand what drives your business, then this
book can help you get started. You need access to SAS Enterprise Guide or SAS Enterprise Miner
software; we provide you with example data to get started, but you will need data to analyze. An
understanding of basic statistics is helpful, but not required.
Organization
The book begins by helping you determine and structure the objective of your analysis in
accordance with the goals and objectives of your organization or department.
Chapter 2 describes types and sources of data for analysis. Chapter 3 offers an overview of
common business analyses, covering both descriptive and predictive analysis. Chapter 4 shows you
how to construct a data set for analysis. Chapter 5 details step-by-step instructions for a simple
descriptive analysis. Chapter 6 offers the same level of detail for a typical market analysis.
Chapters 7 and 8 offer a step-by-step guide to cluster and tree analyses, respectively. Each chapter
concludes with a section headed “Notes from the Field,” which offers related business advice and
leadership tips.
To conclude, Chapter 9 brings several concepts together in a full step-by-step case study for
building and comparing predictive models, culminating in final “Notes from the Field.”
viii
Examples
SAS Institute and SAS Press provide access to software updates and the author’s example data sets
so that you can practice the examples in this book.
Software Used
The software packages used in the writing of this book are SAS Enterprise Guide 6.1 M1 and SAS
Enterprise Miner 13.1. Although these are the latest versions available at the time of publication,
new features will appear in later releases. Visit the SAS Products and Solutions webpage for
updates and enhancements to all SAS system software at http://www.sas.com/en_us/software/all-
products.html.
Data Sets
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Additional Help
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is particularly useful to both the novice and the seasoned SAS user is its Knowledge Base.
ix

Search for relevant notes in the “Samples and SAS Notes” section of the Knowledge Base at
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