Introduction
Data Analysis Expressions (DAX) in Power BI encompass a collection of formulas, functions, operators, and constants that enable users to create measures, dimensions, and custom tables. DAX empowers data analysts to perform advanced calculations, discover hidden patterns in unstructured datasets, and establish relationships between different data variables. These expressions are evaluated from the innermost to the outermost function, utilizing conditional statements, value references, formulas, loops, and more.
Data Types in Power BI DAX Functions
Power BI DAX functions primarily operate on two data types:
- Numeric: This category includes decimal numbers, currency values, integers, and similar types.
- Non-numeric: It comprises strings, binary objects, and other non-numeric data.
Importance of DAX in Power BI
Understanding DAX functions in Power BI is crucial for implementing data transformation and visualization functionalities. While basic knowledge of the Power BI interface allows users to create decent reports and share them online, calculations and dimensional analysis require familiarity with Power BI DAX functions. For instance, calculating growth percentages and visualizing them across different regions over the years can help compare data and identify business problems and potential solutions.
Prerequisites
Implementing DAX expressions shares similarities with creating formulas in Microsoft Excel. While prior experience with Excel spreadsheets can be helpful, it is not mandatory to use DAX in Power BI. However, understanding the fundamentals of measures, statistics, probability, and Power BI Desktop is necessary to comprehend the formulas and calculations involved.
DAX Formula Syntax
Breaking down a DAX statement into individual elements facilitates comprehension. It is important to study the syntax of DAX expressions and be able to create new ones according to specific requirements. Consider the following example to understand DAX syntax:
Test Column: The name of the new measure.
= Sign: Denotes the beginning of the DAX formula.
[Units Sold] and [Manufacturing Price]: Arguments or columns whose values are used to generate the output.
*: The multiplication operator multiplies the values of the two-column variables.
[Segment]: Represents the classification of the formula. Calculated columns must have at least one.
DAX Calculation Types
DAX in Power BI encompasses two calculation types:
- Calculated Columns: These columns merge new columns into existing ones with applied filters. They can be created from the Modeling tab in Power BI Desktop by specifying column names and their corresponding formulas.
- Calculated Measures: Measures allow the creation of fields with aggregate values such as averages, ratios, percentages, etc. Similar to calculated columns, measures are created from the Modeling tab in Power BI Desktop.
DAX Functions
DAX functions in Power BI are predefined formulas used to calculate arguments in a specific order. These arguments can be numbers, constants, texts, other functions or formulas, and logical values (True or False). DAX functions operate on fields, columns, or tables rather than individual values. However, if DAX functions need to be applied to individual values, filters must be created within the formula. Some important points about DAX functions include:
- DAX functions can be applied to separate rows without filters, allowing calculations based on the context of each row.
- Time intelligence functions in DAX facilitate calculations involving time and date ranges.
- DAX functions may return entire tables, which can be used as input for other DAX functions, but these output tables cannot be displayed directly.
Types of DAX Functions
Power BI DAX functions encompass various categories, including:
- Date and Time Functions: Used to calculate dates and periods in DateTime format, similar to Excel functions. Examples include CALENDAR, DATEDIFF, NOW, and DATEVALUE.
- Time Intelligence Functions: Enable time-based calculations.