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Index
Cover image
Title page
Table of Contents
Copyright
Foreword
How to Use This Book
Acknowledgments
Part I. Concepts and Context
Chapter 1. The Business Demand for Data, Information, and Analytics
Just One Word: Data
Welcome to the Data Deluge
Taming the Analytics Deluge
Too Much Data, Too Little Information
Data Capture versus Information Analysis
The Five Cs of Data
Common Terminology from our Perspective
Part II. Business and Technical Needs
Chapter 2. Justifying BI: Building the Business and Technical Case
Why Justification is Needed
Building the Business Case
Building the Technical Case
Assessing Readiness
Creating a BI Road Map
Developing Scope, Preliminary Plan, and Budget
Obtaining Approval
Common Justification Pitfalls
Chapter 3. Defining Requirements—Business, Data and Quality
The Purpose of Defining Requirements
Goals
Deliverables
Roles
Defining Requirements Workflow
Interviewing
Documenting Requirements
Part III. Architectural Framework
Chapter 4. Architecture Framework
The Need for Architectural Blueprints
Architectural Framework
Information Architecture
Data Architecture
Technical Architecture
Product Architecture
Metadata
Security and Privacy
Avoiding Accidents with Architectural Planning
Do Not Obsess over the Architecture
Chapter 5. Information Architecture
The Purpose of an Information Architecture
Data Integration Framework
DIF Information Architecture
Operational BI versus Analytical BI
Master Data Management
Chapter 6. Data Architecture
The Purpose of a Data Architecture
History
Data Architectural Choices
Data Integration Workflow
Data Workflow—Rise of EDW Again
Operational Data Store
Chapter 7. Technology & Product Architectures
Where are the Product and Vendor Names?
Evolution Not Revolution
Technology Architecture
Product and Technology Evaluations
Part IV. Data Design
Chapter 8. Foundational Data Modeling
The Purpose of Data Modeling
Definitions—The Difference Between a Data Model and Data Modeling
Three Levels of Data Models
Data Modeling Workflow
Where Data Models Are Used
Entity-Relationship (ER) Modeling Overview
Normalization
Limits and Purpose of Normalization
Chapter 9. Dimensional Modeling
Introduction to Dimensional Modeling
High-Level View of a Dimensional Model
Facts
Dimensions
Schemas
Entity Relationship versus Dimensional Modeling
Purpose of Dimensional Modeling
Fact Tables
Achieving Consistency
Advanced Dimensions and Facts
Dimensional Modeling Recap
Chapter 10. Business Intelligence Dimensional Modeling
Introduction
Hierarchies
Outrigger Tables
Slowly Changing Dimensions
Causal Dimension
Multivalued Dimensions
Junk Dimensions
Value Band Reporting
Heterogeneous Products
Alternate Dimensions
Too Few or Too Many Dimensions
Part V. Data Integration Design
Chapter 11. Data Integration Design and Development
Getting Started with Data Integration
Data Integration Architecture
Data Integration Requirements
Data Integration Design
Data Integration Standards
Loading Historical Data
Data Integration Prototyping
Data Integration Testing
Chapter 12. Data Integration Processes
Introduction: Manual Coding versus Tool-Based Data Integration
Data Integration Services
Part VI. Business Intelligence Design
Chapter 13. Business Intelligence Applications
BI Content Specifications
Revise BI Applications List
BI Personas
BI Design Layout—Best Practices
Data Design for Self-Service BI
Matching Types of Analysis to Visualizations
Chapter 14. BI Design and Development
BI Design
BI Development
BI Application Testing
Chapter 15. Advanced Analytics
Advanced Analytics Overview and Background
Predictive Analytics and Data Mining
Analytical Sandboxes and Hubs
Big Data Analytics
Data Visualization
Chapter 16. Data Shadow Systems
The Data Shadow Problem
Are There Data Shadow Systems in Your Organization?
What Kind of Data Shadow Systems Do You Have?
Data Shadow System Triage
The Evolution of Data Shadow Systems in an Organization
Damages Caused by Data Shadow Systems
The Benefits of Data Shadow Systems
Moving beyond Data Shadow Systems
Misguided Attempts to Replace Data Shadow Systems
Renovating Data Shadow Systems
Part VII. Organization
Chapter 17. People, Process and Politics
The Technology Trap
The Business and IT Relationship
Roles and Responsibilities
Building the BI Team
Training
Data Governance
Chapter 18. Project Management
The Role of Project Management
Establishing a BI Program
BI Assessment
Work Breakdown Structure
BI Architectural Plan
BI Projects Are Different
Project Methodologies
BI Project Phases
BI Project Schedule
Chapter 19. Centers of Excellence
The Purpose of Centers of Excellence
BI COE
Data Integration Center of Excellence
Enabling a Data-Driven Enterprise
Index
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