DAX, which stands for Data Analysis Expressions, is a formula language used in Power BI, Microsoft Excel, and SQL Server Analysis Services (SSAS) Tabular models. DAX is specifically designed for working with relational data and performing calculations, aggregations, and data manipulation tasks in Power BI.
- Calculations: DAX allows users to create calculated columns and measures within Power BI datasets. Calculated columns are derived columns created based on existing data columns, while measures are dynamic calculations performed on the fly, usually based on aggregations or conditions.
- Aggregations: DAX provides functions for performing aggregations such as SUM, AVERAGE, MIN, MAX, and COUNT on columns or tables of data. These aggregation functions can be used to summarize data and generate insights in Power BI visualizations
- Filtering and Slicing: DAX includes functions for applying filters and slicing data within calculations. Users can filter data based on specific criteria or conditions using functions like FILTER, ALL, and RELATEDTABLE.
- Time Intelligence: DAX offers specialized functions for performing time-related calculations and analysis, such as calculating year-to-date, month-to-date, or quarter-to-date values, comparing data over different time periods, and handling fiscal calendars.
- Statistical Analysis: DAX provides functions for performing statistical analysis and calculations, such as calculating moving averages, standard deviations, variance, and percentiles.
- Data Modeling: DAX plays a crucial role in defining relationships between tables, creating hierarchies, and building complex data models in Power BI. It allows users to define calculated tables, which are tables generated based on DAX expressions.
- Custom Business Logic: DAX allows users to implement custom business logic and calculations based on specific requirements or business rules. Users can create complex formulas and expressions to address unique analytical needs within their Power BI reports and dashboards.
