Project Management And Requirements
The Business Life Cycle
Project Planning and Management
Collecting the Requirements
Designing The Data Warehouse—Part 1
The Case For Dimensional Modeling
Fact and Dimension Tables
Drilling Up and Down
Primary, Foreign, and Surrogate Keys
Additive, Semiadditive, and Nonadditive Facts
Families of Fact Tables
Factless Fact Tables
Designing The Data Warehouse—Part 2
Extended Dimension Table Designs
Extended Fact Table Designs
Advanced Relational OLAP Querying and Reporting
Building Dimensional Models
Getting Started With the Matrix Method
Managing the Dimensional Modeling Project
Data Warehouse Architecture
Defining the Columns
Defining the Rows
Logical and Physical Models
Services and Data Stores
Flow From Source System to User Desktop
Key Technical Architecture Features
Evolution of the Data Warehouse Architecture
Back Room Technical Architecture
Back Room Data Stores
Back Room Services
Back Room Asset Management
Front Room Technical Architecture
Front Room Data Stores
Front Room Services
Infrastructure And Metadata
Infrastructure
Metadata and the Metadata Catalog
Creating The Architecture Plan And Selecting Products
Creating the Architecture
A Product Evaluation Methodology
Designing Aggregates
Deciding What to Aggregate
Processing Aggregates
Administering the Aggregates
An Aggregate Navigation System
An Aggregate Navigation Algorithm
Completing The Physical Design
Develop Standards
Develop the Physical Model
Develop the Initial Index Plan
Design and Build the Database Instance
Develop the Physical Storage Structure
Implement Usage Monitoring
Data Staging
Plan Effectively
Dimension Table Staging
Fact Table Loads and Warehouse Operations
Data Quality and Cleansing
Building End User Applications
Role of the End User Application
Application Specification
End User Application Development
Planning The Deployment
Determine Desktop Installation Readiness
Develop the End User Education Strategy
Develop an End User Support Strategy
Develop the Deployment Release Framework
Document the Deployment Strategy
Maintenance And Growth Of The Data Warehouse
Manage the Existing Data Warehouse Environment
Prepare for Data Warehouse Growth and Evolution