Efficient Data Modeling with the Star Schema in Power BI
Create, optimize and use data models
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Machine Learning Engineer
Basics of data modeling
- Data modeling in relational SQL databases.
- Data Modeling in Power BI.
- The strengths and weaknesses of the flat table as a data model.
The Star Schema as the Standard for High-Performance Data Models
- Improved evaluation options.
- Simplifying DAX commands.
- Optimizing memory usage and performance.
Importing Data with Power Query
- Creation of dimension and fact tables.
- Clean and transform data, for example, using the unpivot feature.
- Differentiation between joins in Power Query and relationships in Power Pivot.
Building Data Models Using the Star Schema
- Understand and apply relationships in the Power BI data model (1:1, 1:n, and n:m).
- Active and inactive connections, e.g. for date tables.
- Multi-fact scheme for complex target/actual comparisons.
Best practices for data modeling
- Best practices for maintainable and high-performance data models.
- Identify and avoid common modeling errors.
AI Support with Microsoft Copilot and Anthropic Claude
- Copilot and Claude in Power BI and Excel: Use a prompt to have them generate and explain the Power Query steps for data modeling.
- Copilot and Claude as sparring partners for modeling decisions: building the star schema, naming dimension and fact tables, and documenting the data model.
- Prompting Basics: Distinguishing Between Good and Poor AI Outputs and Critically Evaluating Suggestions.
- Data Privacy and the Limits of AI Use in Data Modeling.
Practical exercises and case studies
- Develop data models using real-world examples.
- Discussion of selected solutions and exchange of experiences.
- Open Q&A session.
Please bring your own laptop to the training . You can find more detailed installation instructions under Methods.
In your online learning environment, you will find useful information, downloads and extra services for this training course once you have registered.
In this training
- you'll take your data modeling skills with Power BI and Excel to the next level.
- You'll develop your own data models to make reports and dashboards more efficient.
- You'll understand the importance of relationships between tables and learn how to use them effectively.
- You'll gain new insights through hands-on case studies and exercises.
- You can use AI assistants like Copilot and Claude efficiently to create and document data models more quickly.
Presentations, practical examples, and independent exercises on the computer, sample solutions, tips, and tricks. Throughout training , we training AI assistants (Microsoft Copilot and Claude) as practical tools and test them directly during the exercises.
Due to the workshop character of the seminar, questions, tasks and own suggestions for solutions are very welcome, so that a high level of practical relevance is guaranteed.
To take part in the training , you will need your own laptop with Microsoft Excel installed (Office 365 is recommended) and Power BI integrated (the latest version is recommended).
For the AI exercises, access to Microsoft Copilot and/or Claude is helpful but not required to participate; however, we’ll also walk you through the key steps using sample examples.
controllers and users from other areas who want to integrate complex data structures into reports and dashboards.
Good basic knowledge of MS Excel and regular use of pivot tables are required. The training is not suitable for Excel newcomers .
Prior knowledge of Power BI and Power Query is required. It is helpful to have completed the training Power BI—The Modern Business Intelligence Tool" training .
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