Adding DAX calculations to Power BI semantic models allows you to define custom logic within your data model, to enable deeper analysis and data-driven business decisions.
In this module, you learn how to:
- Create calculated tables.
- Create calculated columns.
- Create measures using DAX.
Good modeling practices lead to scalable semantic models that simplify analysis and reporting of large, complex data, enhancing Power BI reports for an optimal user experience.
By the end of this module, you'll be able to:
- Choose appropriate storage modes for your semantic model.
- Enable large semantic model storage format and incremental refresh.
- Create relationships between tables in a semantic model.
- Design dynamic elements to extend calculations in a semantic model.
Performance optimization, also known as performance tuning, involves making changes to the current state of the semantic model so that it runs more efficiently. Essentially, when your semantic model is optimized, it performs better.
By the end of this module, you learn how to:
- Review the performance of measures, relationships, and visuals.
- Use variables to improve performance and troubleshooting.
- Improve performance by reducing cardinality levels.
- Optimize DirectQuery models with table level storage.
- Create and manage aggregations.
Create Power BI assets for your analytics environment for structure and consistency, such as Power BI template and project files. Reusable assets and using the XMLA endpoint support application lifecycle management, including continuous integration and deployment.
Upon completion of this module, you should be able to:
- Create core and specialized semantic models.
- Create Power BI Template and Power BI Project files.
- Use lineage view and endorse data assets in Power BI service.
- Use XMLA endpoint to connect semantic models.
Enforce model security in Power BI using row-level security and object-level security.
By the end of this module, you’ll be able to:
- Restrict access to Power BI model data with RLS.
- Restrict access to Power BI model objects with OLS.
- Apply good development practices to enforce Power BI model security.

Syllabus

Create DAX calculations in semantic models
- Introduction
- Create calculated tables
- Create calculated columns
- Understand implicit measures
- Create explicit measures
- Use iterator functions
- Exercise - Create DAX calculations
- Check your knowledge
- Summary
Design scalable semantic models
- Introduction
- Choose the best storage mode
- Configure semantic models for large data
- Work with relationships
- Write DAX for readability with complex calculations
- Create dynamic calculation elements
- Exercise - Design a scalable semantic model
- Module assessment
- Summary
Optimize a model for performance in Power BI
- Introduction to performance optimization
- Describe semantic model optimization techniques
- Review performance of measures, relationships, and visuals
- Use variables to improve performance and troubleshooting
- Reduce cardinality
- Optimize DirectQuery models with table level storage
- Create and manage aggregations
- Check your knowledge
- Summary
Create and manage Power BI assets
- Introduction
- Create reusable Power BI assets
- Manage development lifecycle for Power BI assets
- Use lineage view and endorse data assets
- Manage a Power BI semantic model using XMLA endpoint
- Exercise: Create reusable Power BI assets
- Module assessment
- Summary
Enforce Power BI model security
- Introduction
- Restrict access to Power BI model data
- Restrict access to Power BI model objects
- Apply good modeling practices
- Exercise: Enforce model security
- Module assessment
- Summary