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Power BI Data Modelling Course Outline

Who should attend

Data Modelling is the fundamental skill needed to produce sophisticated analyses and powerful reports. Data Modelling is about the arrangement and relationships of several data tables. This course is aimed at people who have some experience of using Power BI and who want to build or review a data model.

Course Length

1 day (short version) or 2 days (preferred, full version)

Learning Objectives

Attendees will be able to use Power BI’s data modelling features to design and arrange their data into well-known dimensional modelling patterns resulting in better reports and dashboards. They will be able to review and critique data models.

Pre-requisites

A basic familiarity with Power BI, for example gained on the foundation and intermediate courses.

Course Content

This is a practical hands-on course. Attendees will build Power BI data models and visualisations to check they are working as expected. The course covers thew structure of a dingle table, arranging tables into a model, date tables, and using AI tools to help with data modelling.

The structure of a single table

• Tables, columns and data types
• The grain of a table, and why this is important
• Primary and foreign keys
• Unique and distinct values
• Discrete and continuous variables

Arranging several tables into a dimensional data model

• Relationships between tables
• Fact and dimension tables
• Star schemas (and their advantages)
• Snowflake schemas
• Role playing dimensions

Date Tables

Date (calendar) tables are of fundamental importance in data models and every Power BI data model should have a proper date table. This section covers:

• Why date tables are important
• How to create a date table

Use AI tools to help with data modelling

• Use AI assistant, such as ChatGPT or Clause, to help design and build data models
• Review and improve Power BI semantic models with the help of AI tools like Claude and GitHub Copilot and the Power BI Model Context Protocol (MCP) server.

Example Lab Exercise

One of the possible case studies for this course is some fictional data about store sales & profit by date, customer, geography, product. More details are here. By the end of the course, you will have built a data model similar to the screenshot below.