search for books and compare prices
Tables of Contents for Building a Data Warehouse for Decision Support
Chapter/Section Title
Page #
Page Count
Preface
xix
4
Preface to the First Edition
xxiii
6
Acknowledgments
xxix
14
About the Authors
xxxiii
4
Other Contributors to This Book
xxxvii
Chapter 1 Let's Start with the Basics
1
14
WHAT IS A DECISION SUPPORT SYSTEM?
3
1
UNDERSTANDING OPERATIONAL VERSUS ANALYTICAL PROCESSING
3
2
Tips From the Trenches 1.1: CHARGEBACKS AND INTERNAL COST ALLOCATIONS
5
1
WHAT IS A DATA WAREHOUSE?
6
1
SUMMARY
6
3
CASE STUDY 1: Ongoing Data Warehouse Development at Anthem Blue Cross & Blue Shield
9
6
Chapter 2 Understanding Terms and Technology
15
14
ANALYTICAL PROCESSING
17
1
OPERATIONAL PROCESSING
17
1
DECISION SUPPORT SYSTEMS
17
1
DATA WAREHOUSE
18
1
DATA MART
18
1
ENVIRONMENT FOR DATA ACCESS
18
1
ARCHITECTURE
19
1
TECHNICAL INFRASTRUCTURES
20
1
SOURCE AND TARGET DATA
20
1
LEVELS OF USERS
20
2
CLASSES OF TOOLS
22
1
DECISION SUPPORT SYSTEM (DSS) APPLICATIONS
23
1
DATA INTEGRATION
23
1
SYNONYMS
24
1
HOMONYMS
24
1
ANALOGS
24
1
DATA TRANSFORMATION
24
1
DATA CONVERSION TOOLS
24
1
MIDDLEWARE TOOLS
25
1
METADATA
25
1
STAR SCHEMA
26
1
HIERARCHIES
26
1
GRANULARITY
26
1
DATABASE GATEWAY
27
1
MEGABYTES, GIGABYTES, AND TERABYTES
27
1
DECISION SUPPORT DEVELOPMENT CYCLE
27
1
SUMMARY
28
1
Chapter 3 Understanding Architecture and Infrastructures
29
22
THE TASK AT HAND
31
1
UNDERSTANDING DATA WAREHOUSE ARCHITECTURE
32
1
THE CHARACTERISTICS OF DATA WAREHOUSE ARCHITECTURE
32
3
Data Is Extracted from Source Systems, Databases, or Files
32
2
The Data from the Source Systems Is Integrated before Being Loaded into the Data Warehouse
34
1
The Data Warehouse Is a Separate Read-Only Database Designed Specifically for Decision Support
34
1
Users Access the Data Warehouse via a Front End Tool or Application
35
1
EXPANDING THE GENERIC DATA WAREHOUSE ARCHITECTURE
35
5
UNDERSTANDING THE RELATIONSHIP OF ARCHITECTURE AND INFRASTRUCTURES
40
5
ARCHITECTURE AND INFRASTRUCTURES AS A SEPARATE PROJECT
45
2
Tips From the Trenches 3.1: ARCHITECTURE AND INFRASTRUCTURES
46
1
AND THE ANSWER IS...
47
1
SUMMARY
48
3
Chapter 4 Critical Success Factors
51
38
A FOCUS ON SUCCESS
53
1
HOW IS A DATA WAREHOUSE DIFFERENT?
53
7
A Data Warehouse Incorporates Operational and Historical Data
53
1
Periodic Updates Rather than Real-Time
54
1
Service Levels for High Availability
55
2
Interactive Exploration of Information by Business End Users
57
1
Database Structures
58
2
WHY WOULD I WANT A DATA WAREHOUSE?
60
3
Total View of the Organization
60
1
The Past Is the Best Predictor of the Future
61
1
Single Version of Organizational Truth
62
1
Support for DSS without Impacting Operational Systems
62
1
TYPICAL APPLICATION DEPLOYMENTS
63
11
Fraud Detection
64
1
Target Marketing
65
1
Profitability Analysis
66
1
Customer Retention
67
2
Inventory Management
69
2
Credit Risk Analysis
71
1
Long-Term Value Assessment
72
1
Pricing
73
1
KEY CRITICAL SUCCESS FACTORS
74
7
Focus on the Business, Not the Technology
75
1
Rapid Turnaround on Deliverables
76
4
End Users on the Implementation Team
80
1
SUMMARY
81
4
CASE STUDY 2: EPA Intranet Helps Policy Makers Protect the Environment
85
4
Chapter 5 The Decision Support Life Cycle
89
20
LIFE CYCLES FOR SYSTEM DEVELOPMENT
91
1
ISSUES AFFECTING THE DECISION SUPPORT LIFE CYCLE
91
1
THE DECISION SUPPORT LIFE CYCLE IN AN ARCHITECTED ENVIRONMENT
92
1
THE PHASES OF THE DECISION SUPPORT LIFE CYCLE (DSLC)
93
14
Phase 1: Planning
93
2
Phase 2: Gathering Data Requirements and Modeling
95
3
Gathering Data Requirements
96
1
Data Modeling
97
1
Phase 3: Physical Database Design and Development
98
1
Phase 4: Data Sourcing, Integration, and Mapping
99
2
Phase 5: Populating the Data Warehouse
101
2
Tips from the Trenches 5.1: AVAILABILIY OF DATA
102
1
Phase 6: Automating Data Load Procedures
103
1
Phase 7: Creating the Starter Set of Reports
103
1
Phase 8: Data Validation and Testing
104
1
Phase 9: Training
105
1
Phase 10: Rollout
106
1
SUMMARY
107
2
Chapter 6 Getting Started with Data Warehouse Development
109
24
THE PROOF IS IN THE PILOT
111
3
Clarify the Purpose and Goal of the Pilot Project
111
2
Treat the Pilot like a Development Project
113
1
Building on the Pilot
113
1
CHOOSING A BUSINESS AREA FOR DATA WAREHOUSE DEVELOPMENT
114
2
Tips from the Trenches 6.1: CHOOSING A BUSINESS AREA
115
1
ENSURING A SUCCESSFUL DATA WAREHOUSE
116
6
Tips from the Trenches 6.2: BUILDING A SUCCESSFUL DATA WAREHOUSE "THE BIG EIGHT"
117
1
Be Clear on the Business Objective of Your Data Warehouse
117
1
Understand the Chosen Data Warehouse Architecture
118
1
Make Sure the Technical Infrastructures Are in Place or Being Put in Place
118
1
Clarify the Project Team's Responsibility and Final Deliverable
118
2
Make Sure the Members of the Project Team and the Users Understand the Difference between Operational and Decision Support Data
120
1
Get the Correct Training
120
1
Get the Right Resources
121
1
Choose Front End Data Access Software Based on User Needs and Abilities
122
1
SUMMARY
122
3
CASE STUDY 3: Moving through the Obstacles to Implementation
125
8
Chapter 7 Gathering Data Requirements
133
18
A PROPER MINDSET
135
1
USER INTERVIEWS
135
9
The Purpose of Interviews
135
1
Setting up Successful Interviews
136
1
Who to Interview
136
2
Key End Users and Analysts from the Target Business Functions
137
1
Managers from the Target Business Functions
137
1
Analysts and Users from Related Business Functions
137
1
Managers from Related Business Functions
137
1
Executives
138
1
What to Ask End Users
138
3
Job Responsibilities
138
1
Current Analysis
138
1
What You Receive
138
1
What You Create
139
1
Ad Hoc Analysis
139
1
Business Analyses
140
1
Data Specific Information
140
1
Wish List Information
140
1
Other Data Sourcing Information
140
1
Business Hierarchies
140
1
What Have You Missed?
141
1
What to Ask Executives
141
1
Documenting What You Heard
142
2
What You Have to Know for DSS
144
1
FACILITATION VIA ALIGNMENT
144
1
DEVELOPING THE DATA MODEL
145
3
Dimensional Business Model
145
3
Tips from the Trenches 7.1: THE BASICS OF DATA MODELING
147
1
Logical Data Model
148
1
SUMMARY
148
3
Chapter 8 Data Integration
151
38
INTRODUCTION
153
1
THE METAMORPHOSIS OF DATA TO INFORMATION
153
1
DEFINING DATA VERSUS INFORMATION
154
1
DATA INTEGRATION
154
2
DATA ARCHITECTURE
156
1
Tips from the Trenches 8.1: DATA ARCHITECTURE TO SUPPORT CHANGE
156
1
METADATA
157
1
THE DATA INTEGRATION PROCESS
158
1
DATA SOURCING
159
1
DATA CONSOLIDATION
160
1
UNDERSTANDING THE PROCESS OF DATA CONSOLIDATION
161
11
Analyze Source Data Documentation (Metadata)
161
2
Tips from the Trenches 8.2: SOURCE DOCUMENTATION QUALITY
162
1
"Flatten Out" the Data into Logical Records
163
2
Tips from the Trenches 8.3: FLATTENING FILES
164
1
Perform Domain Analysis
165
2
Tips from the Trenches 8.4: GET REPRESENTATIVE SET OF DATA TO ANALYZE
166
1
Determine the Primary Keys
167
3
Tips from the Trenches 8.5: DATA INTEGRATION RESOURCES
168
2
Determine Foreign Keys
170
2
Tips from the Trenches 8.6: IDENTIFYING SYNONYMS ACROSS SOURCE FILES
171
1
ADDITIONAL DATA ANALYSIS NEEDED FOR DATA CONSOLIDATION
172
9
Subject Area Analysis
172
1
Synonyms, Homonyms, and Analogs
173
2
Analyzing Data to Integrate It Into An Existing Data Warehouse
175
1
Tips from the Trenches 8.7: DATA ANALYSIS AND INTEGRATION AS ONGOING PROCESSES
175
1
Understanding Business Rules and Nuances of Meaning
176
3
Data-Driven Analysis
179
2
Tips from the Trenches 8.8: DOCUMENTING BUSINESS RULES
179
2
DATA CONVERSION
181
2
Map Source File Attributes to the Data Warehouse Physical Data Structure
181
1
Map Source Attribute Allowable Values to Target Value
182
1
Specify Default Values
182
1
Write Conversion Specifications
182
1
DATA POPULATION
183
3
Tips from the Trenches 8.9: DATA INTEGRATION TOOLS
183
1
Write Conversion Programs
184
1
Perform Testing
184
1
Determine Exception Processing
184
1
Collect Statistics
185
1
Perform Quality Assurance
185
1
Perform Stress Tests
185
1
SUMMARY
186
3
Chapter 9 Designing the Database for a Data Warehouse
189
28
DECISION SUPPORT DATABASES
191
1
STAR SCHEMA DATABASE DESIGN
191
2
The Benefits of Using a Star Schema
192
1
Understanding Star Schema Design--Facts and Dimensions
192
1
VARIETIES OF STAR SCHEMAS
193
8
How to Read the Diagrams
193
1
Simple Star Schemas
193
2
Tips from the Trenches 9.1: UNDERSTANDING FACTS AND DIMENSIONS
194
1
Multiple Fact Tables
195
2
Outboard Tables
197
1
Variations of a Star Schema
198
1
Multistar Schemas
199
2
A SALAD DRESSING EXAMPLE
201
3
Understanding the Available Data, Browsing the Dimension Tables
202
1
Using Table Attributes
203
1
Creating Attribute Hierarchies
204
1
AGGREGATION
204
3
DENORMALIZATION
207
1
LIMITATIONS OF THE STAR SCHEMA
208
1
DATA WAREHOUSE DATABASE DESIGN EXAMPLES
209
3
Reservation Database
209
1
Investment Database
209
3
Health Insurance Database
212
1
Putting It All Together
212
1
SUMMARY
212
5
Chapter 10 Successful Data Access
217
28
GENERAL UNDERSTANDING OF DATA ACCESS
219
1
WHAT ARE YOU REALLY TRYING TO DO?
219
1
TYPES OF ACCESS
220
1
LEVELS OF USERS
221
1
WHAT IS A DSS APPLICATION?
222
2
DATA ACCESS CHARACTERISTICS
224
9
Visualization of the Data Warehouse
224
1
User Formulates Request
224
1
Viewing the Results
224
3
Metrics and Calculated Metrics
225
1
Constraining a Request
226
1
How the Request is Processed
227
1
Presentation of Results
227
4
Reports
230
1
Graphs
230
1
Maps
231
1
Communicate Findings
231
1
Advanced Features
231
1
Advanced Analytics
231
1
Batch Query Processing
232
1
DSS Application Development
232
1
CLASSES OF TOOLS
233
2
Data Access Query Tools
233
1
Report Writers
233
1
Multidimensional Database Management Systems (MDBMS)
233
1
Advanced DSS Tools
234
1
Executive Information Systems (EISs)
234
1
Tiered Architectures
234
1
SELECTING TOOLS FOR YOUR ORGANIZATION
235
3
One Tool Fits All?
235
1
The Request for Proposal (RFP)
236
1
Key Considerations
236
1
What Matters to You?
237
1
Selecting a Vendor, Not Just a Tool
237
1
SUMMARY
238
3
CASE STUDY 4: Selecting a Front End to the Data Warehouse
241
4
Chapter 11 Training, Support, and Rollout
245
8
TRAINING
247
1
SUPPORT
248
1
INTERNAL MARKETING OF THE DATA WAREHOUSE
249
1
DATA WAREHOUSE MARKETING IDEAS
249
2
Target Specific Groups
249
1
Get Clear and Visible Management Support
250
1
Provide Visible Opportunities
250
1
Be Proactive
250
1
Create a Publication
251
1
PLANNING A ROLLOUT: DEPLOYMENT
251
1
Phased Rollout Approach
251
1
Logistics of a Rollout
251
1
SUMMARY
252
1
Chapter 12 Metadata
253
20
INTRODUCTION
255
4
Using MetaData for Change Management
255
1
Metadata and Data Administration
256
1
Metadata Directory
256
3
Tips from the Trenches 12.1: A CAUTIONARY NOTE
258
1
Metadata Administration in Practice
259
1
CHANGE MANAGEMENT
259
5
Understanding Versions and Releases
259
1
Metrics for Change Management
260
3
Tips From the Trenches 12.2: THE SKILLS OF A CHANGE MANAGER
263
1
A REALISTIC APPRAISAL OF METADATA MANAGEMENT WITHIN CORPORATIONS
264
1
UNDERSTANDING TYPES OF METADATA
265
1
Metadata for Data Integration
265
1
Metadata for Data Transformation
265
1
HOW TO APPROACH A SHORT-TERM SOLUTION FOR YOUR PROJECT
266
4
Other Uses of the Data Transformation Metadata
268
1
Using Data Transformation Metadata for Application Deployment
269
1
SUMMARY
270
3
Appendix: Consulting Companies Assisting in the Development of this Book
273
6
Index
279