Course Description

This two-day Dimensional Modelling for Business Intelligence training course shows participants how to develop and use dimensional models of data for Data Warehouse and Business Intelligence analysis and reporting purposes.

After completing this course, students will be able to:

  • Describe and use dimensional models. This includes the principles, design, and methods to produce them.
  • Appreciate the need for sound requirements gathering as a prelude to dimensional modelling.
  • Utilise conceptual tools to represent dimensional data in preparation for building the required data structures
  • Understand the relationship of dimensional models to business planning, measurement, and IT architecture.



Familiarity with data design.

Who is this course for?

Dimensional Modelling is suitable for anyone acting (or planning to act) in the role of Data Architect, Data Analyst, Business Systems Analyst, Systems Analyst, Business Analyst or Business Consultant. It is also suitable for other IT professionals who need to understand what Data Architects do and don’t do. It is also relevant for experienced Data Architects who need to update their skills, attend a “refresher”, or simply get some new ideas.


Course content

Business Concepts
A business process
Asset life cycle
Management life cycle
Instrument panels and scorecards
A balanced scorecard
Lagging and leading indicators
Dimensional Concepts
Entity relationship modelling
Dimensional modelling
Why dimensional modelling
The dimensional Model
Facts, dimensions and attributes
Primary, foreign and surrogate keys
Inside Dimension Tables
Drilling down
Large dimensions
Slowly changing dimensions
Inside Fact Tables
Additive, semi-additive and non-additive facts
Value chains, circles and aggregates
‘Factless’ Fact tables
An Architected Approach
Conformed facts and dimensions
Data Mart granularity
The Data Mart matrix
Building dimensional models
Building the matrix
The four steps to define a Data Mart
Design principles
Documenting Dimensional Models
Data Mart matrix
Fact Table Diagrams and details
Dimensional Table Diagram and details
Identifying Source Data
Candidate Data Sources
Surveying the Data
Mapping Source to Target Data
Data Staging
The Data Staging Schematic
Historical and Incremental Loading
ETL Operations and Automation
Impact of IT Architecture
Relevance of Architecture and Planning
Principles of Data Architecture
Data Quality and Improvement
Data Warehouse Architecture
Data warehouse Project Life Cycle