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- Semantic models organize complex data into an intuitive structure, enhancing data visualization and enabling efficient, insightful reporting for better decision-making.
In this module, you learn how to:
- Set modeling options.
- Create and configure relationships.
- Configure table and column properties.
- Create hierarchies.
- Create quick measures.
- Create numeric range and field parameters.
- Data Analysis Expressions (DAX) is a formula language for Power BI that enables you to create calculations, add logic, and enhance data analysis within your reports and semantic models.
In this module, you learn how to:
- Describe the different DAX calculation types.
- Write DAX formulas.
- Describe DAX data types.
- Work with DAX functions.
- Use DAX operators.
- Use DAX variables.
- 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.
- Modifying the filter context in DAX lets you control how calculations evaluate data in Power BI semantic models. Gain deeper insights and tailor your analysis in your reports by choosing exactly what data is included in calculations.
By the end of this module, you'll be able to:
- Describe filter context.
- Use the CALCULATE function to modify filter context.
- Pass filters to the CALCULATE function.
- Pass filter modifiers to the CALCULATE function.
- Perform context transition.
- DAX time intelligence functions in Power BI enable users to analyze and compare data across different time periods, supporting insightful reporting on trends, growth, and performance over time.
By the end of this module, you'll be able to:
- Define time intelligence.
- Use common DAX time intelligence functions.
- Create useful intelligence calculations.
- Calculations in Power BI are necessary to enrich data analysis. Visual calculations simplify complex formulas, enhance performance, and reduce maintenance.
By the end of this module, you'll be able to:
- Understand visual calculations and how they differ from measures.
- Create visual calculations in Power BI Desktop.
- Use parameters in visual calculations.
- 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.
