Data Analysis Expressions, abbreviated as DAX, are formulas or expressions used for calculations and data analysis. These expressions are made up of a variety of functions, operators, and constants that are all evaluated as a single formula to produce the desired results (value or values). DAX formulas are very useful in BI tools like Power BI because they allow data analysts to make the best use of the data sets they already have.

Using the DAX language, analysts can discover new ways to compute data values and generate novel insights.
Take a look at a few key DAX points that will help you understand the concept.

Every line of code in DAX is a function because it is a functional language. A valid DAX expression may contain value references, nested functions, conditional statements, and so on.
In DAX formulas, the two main data types are numeric and non-numeric or others. The numeric data type includes integers, decimals, currency, and other data types. Non-numeric data is made up of binary objects and strings.
The innermost function is evaluated first, then the outermost, and so on. As a result, developing a DAX formula is critical.

When a DAX formula is executed, mixed data type values can be used as inputs, and the conversion is performed automatically. The output values will be transformed using the DAX formula.