TDWI Dimensional Data Modeling Primer: From Requirements to Business Analysis Training in Denmark

The course begins with a comparison of relational and dimensional data organization and provides an example of business questions not readily answered using more traditional data structures of relational modeling. It then illustrates the steps to design analytic solutions, starting from business questions and concluding by demonstrating an OLAP solution. These steps encompass techniques to capture business questions, represent them as a business solution, translate them into a technology solution, and deliver them to those who need information.

• Data architects
• Data mart developers
• Business analysts
• Business intelligence and data warehouse program and project managers

• Concepts of dimensional data modeling
• The relationship between business metrics and dimensional data
• Similarities and differences between relational and dimensional data models
• Requirements-gathering techniques for business metrics and dimensional data
• How to build a logical dimensional model
• How to translate a logical dimensional model to a star schema design
• How dimensional data is used to deliver business analytics and OLAP capabilities

Module One

Dimensional Modeling Concepts

• Dimensional Modeling in Context
  • Business Intelligence Defined
  • Data Warehousing Defined
  • Data Mart Defined
• Dimensional Modeling Basics
  • Dimensional Model Defined
  • Dimensional Modeling Defined
  • Business Metrics and Measures Defined
  • Business Metrics Examples
  • Dimensional Data Models
• Comparing E-R and Dimensional Models
  • A Quick Review of E-R Modeling
  • Introduction to Dimensional Models
  • Relational with Additional Constraints
  • A Basis for Comparison
  • Relational for Transaction Processing
  • Dimensional Data for Business Analysis
  • Conformed Dimensions
• Concepts Summary
  • Review of Some Key Points

Module Two

Requirements Gathering for Dimensional Models

• Business Context for Data Modeling
  • Business Value
  • Business Alignment
  • Business Process Alignment
• Business Questions as Requirements Models
  • A Framework for Business Questions
  • Examples
  • Refining Business Questions
• Fact/Qualifier Analysis
  • From Business Questions to Data Requirements
  • Mapping Business Questions
• Requirements Gathering Summary
  • Process Review

Module Three

Logical Dimensional Data Modeling

• ·Modeling Meters and Measures
  • A Group of Related Business Measures

Modeling Dimensions

• Adding Dimensions from Qualifiers
• Dimension Hierarchy
• Refining the Dimensions
• Completing the Dimensions
• More about Meters and Measures
  • Granularity and the Meter
  • Granularity and the Measures
  • Completing the Meter
• Model Verification
  • Testing the Model

Logical Modeling Summary

• Process Review

Module Four

From Logical Model to Star Schema

• Star Schema Dimensions
  • Naming the Dimensions
  • Modeling Dimension Tables
  • Defining Dimension Table Keys
• Star Schema Fact Tables
  • Modeling the Fact Table
  • Defining the Fact Table Key
  • Supporting Calculated Measures
  • Semi-Additive and Non-Additive Facts
• Star Schema Design Challenges
  • Slowly Changing Dimensions
  • Degenerate Dimensions
  • Junk Dimensions
  • Difficult Situations
• Modeling Process Summary
  • From Business Requirements to Star Schema

Module Five

Dimensional Data and Business Analysis

• Delivering Business Value
  • Data Enabled Business Analysis
  • Collecting, Analyzing, and Using Business Metrics
• Effective Dimensional Modeling
  • Critical Success Factors
  • Mistakes to Avoid
  • References and Learning Resources