DAX syntax

This article describes syntax and requirements for the DAX formula expression language.

Syntax requirements

A DAX formula always starts with an equal sign (=). After the equals sign, you can provide any expression that evaluates to a scalar, or an expression that can be converted to a scalar. These include the following:

  • A scalar constant, or expression that uses a scalar operator (+,-,*,/,>=,...,&&, ...)

  • References to columns or tables. The DAX language always uses tables and columns as inputs to functions, never an array or arbitrary set of values.

  • Operators, constants, and values provided as part of an expression.

  • The result of a function and its required arguments. Some DAX functions return a table instead of a scalar, and must be wrapped in a function that evaluates the table and returns a scalar; unless the table is a single column, single row table, then it is treated as a scalar value.

    Most DAX functions require one or more arguments, which can include tables, columns, expressions, and values. However, some functions, such as PI, do not require any arguments, but always require parentheses to indicate the null argument. For example, you must always type PI(), not PI. You can also nest functions within other functions.

  • Expressions. An expression can contain any or all of the following: operators, constants, or references to columns.

For example, the following are all valid formulas.

Formula Result
= 3 3
= "Sales" Sales
= 'Sales'[Amount] If you use this formula within the Sales table, you will get the value of the column Amount in the Sales table for the current row.
= (0.03 *[Amount])

=0.03 * [Amount]
Three percent of the value in the Amount column of the current table.

Although this formula can be used to calculate a percentage, the result is not shown as a percentage unless you apply formatting in the table.
= PI() The value of the constant pi.

Formulas can behave differently depending on how they are used. You must always be aware of the context and how the data that you use in the formula is related to other data that might be used in the calculation.

Naming requirements

A data model often contains multiple tables. Together the tables and their columns comprise a database stored in the in-memory analytics engine (VertiPaq). Within that database, all tables must have unique names. The names of columns must also be unique within each table. All object names are case-insensitive; for example, the names SALES and Sales would represent the same table.

Each column and measure you add to an existing data model must belong to a specific table. You specify the table that contains the column either implicitly, when you create a calculated column within a table, or explicitly, when you create a measure and specify the name of the table where the measure definition should be stored.

When you use a table or column as an input to a function, you must generally qualify the column name. The fully qualified name of a column is the table name, followed by the column name in square brackets: for examples, 'U.S. Sales'[Products]. A fully qualified name is always required when you reference a column in the following contexts:

  • As an argument to the function, VALUES

  • As an argument to the functions, ALL or ALLEXCEPT

  • In a filter argument for the functions, CALCULATE or CALCULATETABLE

  • As an argument to the function, RELATEDTABLE

  • As an argument to any time intelligence function

An unqualified column name is just the name of the column, enclosed in brackets: for example, [Sales Amount]. For example, when you are referencing a scalar value from the same row of the current table, you can use the unqualified column name.

If the name of a table contains spaces, reserved keywords, or disallowed characters, you must enclose the table name in single quotation marks. You must also enclose table names in quotation marks if the name contains any characters outside the ANSI alphanumeric character range, regardless of whether your locale supports the character set or not. For example, if you open a workbook that contains table names written in Cyrillic characters, such as 'Таблица', the table name must be enclosed in quotation marks, even though it does not contain spaces.


To make it easier to enter the fully qualified names of columns, use the AutoComplete feature in the formula editor.


  • Table names are required whenever the column is from a different table than the current table. Table names must be unique within the database.

  • Table names must be enclosed in single quotation marks if they contain spaces, other special characters or any non-English alphanumeric characters.


  • Measure names must always be in brackets.

  • Measure names can contain spaces.

  • Each measure name must be unique within a model. Therefore, the table name is optional in front of a measure name when referencing an existing measure. However, when you create a measure you must always specify a table where the measure definition will be stored.


Column names must be unique in the context of a table; however, multiple tables can have columns with the same names (disambiguation comes with the table name).

In general, columns can be referenced without referencing the base table that they belong to, except when there might be a name conflict to resolve or with certain functions that require column names to be fully qualified.

Reserved keywords

If the name that you use for a table is the same as an Analysis Services reserved keyword, an error is raised, and you must rename the table. However, you can use keywords in object names if the object name is enclosed in brackets (for columns) or quotation marks (for tables).


Quotation marks can be represented by several different characters, depending on the application. If you paste formulas from an external document or Web page, make sure to check the ASCII code of the character that is used for opening and closing quotes, to ensure that they are the same. Otherwise DAX may be unable to recognize the symbols as quotation marks, making the reference invalid.

Special characters

The following characters and character types are not valid in the names of tables, columns, or measures:

  • Leading or trailing spaces; unless the spaces are enclosed by name delimiters, brackets, or single apostrophes.

  • Control characters

  • The following characters that are not valid in the names of objects:


Examples of object names

The following table shows examples of some object names:

Object Types Examples Comment
Table name Sales If the table name does not contain spaces or other special characters, the name does not need to be enclosed in quotation marks.
Table name 'Canada Sales' If the name contains spaces, tabs or other special characters, enclose the name in single quotation marks.
Fully qualified column name Sales[Amount] The table name precedes the column name, and the column name is enclosed in brackets.
Fully qualified measure name Sales[Profit] The table name precedes the measure name, and the measure name is enclosed in brackets. In certain contexts, a fully qualified name is always required.
Unqualified column name [Amount] The unqualified name is just the column name, in brackets. Contexts where you can use the unqualified name include formulas in a calculated column within the same table, or in an aggregation function that is scanning over the same table.
Fully qualified column in table with spaces 'Canada Sales'[Qty] The table name contains spaces, so it must be surrounded by single quotes.

Other restrictions

The syntax required for each function, and the type of operation it can perform, varies greatly depending on the function. In general, however, the following rules apply to all formulas and expressions:

  • DAX formulas and expressions cannot modify or insert individual values in tables.

  • You cannot create calculated rows by using DAX. You can create only calculated columns and measures.

  • When defining calculated columns, you can nest functions to any level.

  • DAX has several functions that return a table. Typically, you use the values returned by these functions as input to other functions, which require a table as input.

DAX operators and constants

The following table lists the operators that are supported by DAX. For more information about the syntax of individual operators, see DAX operators.

Operator type Symbol and use
Parenthesis operator () precedence order and grouping of arguments
Arithmetic operators + (addition)

- (subtraction/


* (multiplication)

/ (division)

^ (exponentiation)
Comparison operators = (equal to)

> (greater than)

< (less than)

>= (greater than or equal to)

<= (less than or equal to)

<> (not equal to)
Text concatenation operator & (concatenation)
Logic operators && (and)

|| (or)

Data types

You do not need to cast, convert, or otherwise specify the data type of a column or value that you use in a DAX formula. When you use data in a DAX formula, DAX automatically identifies the data types in referenced columns and of the values that you type in, and performs implicit conversions where necessary to complete the specified operation.

For example, if you try to add a number to a date value, the engine will interpret the operation in the context of the function, and convert the numbers to a common data type, and then present the result in the intended format, a date.

However, there are some limitations on the values that can be successfully converted. If a value or a column has a data type that is incompatible with the current operation, DAX returns an error. Also, DAX does not provide functions that let you explicitly change, convert, or cast the data type of existing data that you have imported into a data model.


DAX does not support use of the variant data type. Therefore, when you load or import data into a data model, it's expected the data in each column is generally of a consistent data type.

Some functions return scalar values, including strings, whereas other functions work with numbers, both integers and real numbers, or dates and times. The data type required for each function is described in the section, DAX functions.

You can use tables containing multiple columns and multiple rows of data as the argument to a function. Some functions also return tables, which are stored in memory and can be used as arguments to other functions.

Date and time

DAX stores date and time values using the datetime data type used by Microsoft SQL Server. Datetime format uses a floating-point number where Date values correspond to the integer portion representing the number of days since December 30, 1899. Time values correspond to the decimal portion of a date value where Hours, minutes, and seconds are represented by decimal fractions of a day. DAX date and time functions implicitly convert arguments to datetime data type.


The exact maximum DateTime value supported by DAX is December 31, 9999 00:00:00.

Date and time literal

Beginning with the August 2021 version of Power BI Desktop, DAX date and datetime values can be specified as a literal in the format dt"YYYY-MM-DD", dt"YYYY-MM-DDThh:mm:ss", or dt"YYYY-MM-DD hh:mm:ss". When specified as a literal, use of DATE, TIME, DATEVALUE, TIMEVALUE functions in the expression are not necessary.

For example, the following expression uses DATE and TIME functions to filter on OrderDate:

        [OrderDate] > (DATE(2015,1,9) + TIME(2,30,0)) &&[OrderDate] < (DATE(2015,12,31) + TIME(11,59,59))

The same filter expression can be specified as a literal:

        [OrderDate] > dt"2015-1-9T02:30:00" && [OrderDate] < dt"2015-12-31T11:59:59"


The DAX date and datetime-typed literal format is not supported in all versions of Power BI Desktop, Analysis Services, and Power Pivot in Excel. New and updated DAX functionality are typically first introduced in Power BI Desktop and then later included in Analysis Services and Power Pivot in Excel.