Data Analysis Expressions (DAX) Demystified: Understanding Power BI’s Formula Language

Data Analysis Expressions (DAX) is a powerful formula language essential for unlocking the full analytical capabilities of Power BI and other Microsoft data tools. Designed by Microsoft, DAX is used to perform advanced data analysis and create sophisticated data models.
Where DAX is Used:
- Power BI
- Power Pivot (Excel)
- SQL Server Analysis Services (SSAS) – Tabular models
Though DAX shares a similar syntax with Excel formulas, it is far more powerful and optimized for working with relational data models and large datasets.
With DAX, we can create:
- Calculated columns
- Measures
- Custom tables
DAX formulas use a combination of functions, operators, and values to perform dynamic and complex calculations that enhance the depth of your data insights.
Key Characteristics of Functional Language:
- Pure Functions - Output depends only on input; no side effects.
- Immutability - Variables, once defined, don't change.
- Higher-Order Functions - Functions can take other functions as arguments or return them.
- Declarative Style - Focus on what to do, not how to do it.
- Recursion - Preferred over loops.
- Expressions over statements - Everything return a value.
- Calculated tables
- Calculated columns
- Measures
DAX can also be used to define row-level security (RLS) rules, which are expressions that enforce filters over model tables.
- A calculated table can't connect to external data;
- A calculated table formula must return a table object.
- Calculated table increase the model storage size and they can prolong the data refresh time.
- Useful when a value needs to be stored row-by-row.
- Can create new fields to join with other tables.
- Columns can be used in slicers, filters, visuals, and axes.
- Once defined, they behave like any other column in the model.
- To show calculated results in charts, tables, or matrices.
- To display key performance indicators based on calculations.
- To summarize critical metrics.
- To break down complex data into meaningful insights.
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