Data types in Data Models
In a Data Model, each column has an associated data type that specifies the type of data the column can hold: whole numbers, decimal numbers, text, monetary data, dates and times, and so on. Data type also determines what kinds of operations you can do on the column, and how much memory it takes to store the values in the column.
If you're using the Power Pivot add-in, you can change a column's data type. You might need to do this if a date column was imported as a string, but you need it to be something else. For more information, see Set the data type of a column in Power Pivot.
In this article
Summary of data types
The following table lists data types supported in a Data Model. When you import data or use a value in a formula, even if the original data source contains a different data type, the data is converted to one of these data types. Values that result from formulas also use these data types.
| Data type in Excel | Data type in DAX | Description |
| Whole Number | A 64 bit (eight-bytes) integer value 1, 2 | Numbers that have no decimal places. Integers can be positive or negative numbers, but must be whole numbers between -9,223,372,036,854,775,808 (-2^63) and 9,223,372,036,854,775,807 (2^63-1). |
| Decimal Number | A 64 bit (eight-bytes) real number 1, 2 | Real numbers are numbers that can have decimal places. Real numbers cover a wide range of values: Negative values from -1.79E +308 through -2.23E -308 Zero Positive values from 2.23E -308 through 1.79E + 308 However, the number of significant digits is limited to 15 decimal digits. |
| TRUE/FALSE | Boolean | Either a True or False value. |
| Text | String | A Unicode character data string. Can be strings, numbers or dates represented in a text format. Maximum string length is 268,435,456 Unicode characters (256 mega characters) or 536,870,912 bytes. |
| Date | Date/time | Dates and times in an accepted date-time representation. Valid dates are all dates after January 1, 1900. |
| Currency | Currency | Currency data type allows values between -922,337,203,685,477.5808 to 922,337,203,685,477.5807 with four decimal digits of fixed precision. |
| N/A | Blank | A blank is a data type in DAX that represents and replaces SQL nulls. You can create a blank by using the BLANK function, and test for blanks by using the logical function, ISBLANK. |
1 DAX formulas do not support data types smaller than those listed in the table.
2 If you try to import data that has very large numeric values, import might fail with the following error:
In-memory database error: The '<column name>' column of the '<table name>' table contains a value, '1.7976931348623157e+308', which is not supported. The operation has been cancelled.
This error occurs because Power Pivot uses that value to represent nulls. The values in the following list are synonyms for the null value:
| Value | |
| 9223372036854775807 | |
| -9223372036854775808 | |
| 1.7976931348623158e+308 | |
| 2.2250738585072014e-308 |
Remove the value from your data and try importing again.
Table Data Type
DAX uses a table data type in many functions, such as aggregations and time intelligence calculations. Some functions require a reference to a table; other functions return a table that can then be used as input to other functions. In some functions that require a table as input, you can specify an expression that evaluates to a table; for some functions, a reference to a base table is required. For information about the requirements of specific functions, see DAX Function Reference.
Implicit and explicit data type conversion in DAX formulas
Each DAX function has specific requirements as to the types of data that are used as inputs and outputs. For example, some functions require integers for some arguments and dates for others; other functions require text or tables.
If the data in the column you specify as an argument is incompatible with the data type required by the function, DAX in many cases will return an error. However, wherever possible DAX will attempt to implicitly convert the data to the required data type. For example:
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You can type a date as a string, and DAX will parse the string and attempt to cast it as one of the Windows date and time formats.
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You can add TRUE + 1 and get the result 2, because TRUE is implicitly converted to the number 1 and the operation 1+1 is performed.
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If you add values in two columns, and one value happens to be represented as text ("12") and the other as a number (12), DAX implicitly converts the string to a number and then does the addition for a numeric result. The following expression returns 44: = "22" + 22
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If you attempt to concatenate two numbers, Excel will present them as strings and then concatenate. The following expression returns "1234": = 12 & 34
The following table summarizes the implicit data type conversions that are performed in formulas. Excel performs implicit conversions whenever possible, as required by the specified operation.
Table of Implicit Data Conversions
The type of conversion that is performed is determined by the operator, which casts the values it requires before performing the requested operation. These tables list the operators, and indicate the conversion that is performed on each data type in the column when it is paired with the data type in the intersecting row.
Note: Text data types are not included in these tables. When a number is represented as in a text format, in some cases Power Pivot will attempt to determine the number type and represent it as a number.
Addition (+)
| Operator (+) | INTEGER | CURRENCY | REAL | Date/time |
| INTEGER | INTEGER | CURRENCY | REAL | Date/time |
| CURRENCY | CURRENCY | CURRENCY | REAL | Date/time |
| REAL | REAL | REAL | REAL | Date/time |
| Date/time | Date/time | Date/time | Date/time | Date/time |
For example, if a real number is used in an addition operation in combination with currency data, both values are converted to REAL, and the result is returned as REAL.
Subtraction (-)
In the following table the row header is the minuend (left side) and the column header is the subtrahend (right side).
| Operator (-) | INTEGER | CURRENCY | REAL | Date/time |
| INTEGER | INTEGER | CURRENCY | REAL | REAL |
| CURRENCY | CURRENCY | CURRENCY | REAL | REAL |
| REAL | REAL | REAL | REAL | REAL |
| Date/time | Date/time | Date/time | Date/time | Date/time |
For example, if a date is used in a subtraction operation with any other data type, both values are converted to dates, and the return value is also a date.
Note: Data models also supports the unary operator, - (negative), but this operator does not change the data type of the operand.
Multiplication (*)
| Operator (*) | INTEGER | CURRENCY | REAL | Date/time |
| INTEGER | INTEGER | CURRENCY | REAL | INTEGER |
| CURRENCY | CURRENCY | REAL | CURRENCY | CURRENCY |
| REAL | REAL | CURRENCY | REAL | REAL |
For example, if an integer is combined with a real number in a multiplication operation, both numbers are converted to real numbers, and the return value is also REAL.
Division (/)
In the following table the row header is the numerator and the column header is the denominator.
| Operator (/) (Row/Column) | INTEGER | CURRENCY | REAL | Date/time |
| INTEGER | REAL | CURRENCY | REAL | REAL |
| CURRENCY | CURRENCY | REAL | CURRENCY | REAL |
| REAL | REAL | REAL | REAL | REAL |
| Date/time | REAL | REAL | REAL | REAL |
For example, if an integer is combined with a currency value in a division operation, both values are converted to real numbers, and the result is also a real number.
Comparison operators
In comparison expressions Boolean values are considered greater than string values and string values are considered greater than numeric or date/time values; numbers and date/time values are considered to have the same rank. No implicit conversions are performed for Boolean or string values; BLANK or a blank value is converted to 0/""/false depending on the data type of the other compared value.
The following DAX expressions illustrate this behavior:
=IF(FALSE()>"true","Expression is true", "Expression is false"), returns "Expression is true"
=IF("12">12,"Expression is true", "Expression is false"), returns "Expression is true".
=IF("12"=12,"Expression is true", "Expression is false"), returns "Expression is false"
Conversions are performed implicitly for numeric or date/time types as described in the following table:
| Comparison Operator | INTEGER | CURRENCY | REAL | Date/time |
| INTEGER | INTEGER | CURRENCY | REAL | REAL |
| CURRENCY | CURRENCY | CURRENCY | REAL | REAL |
| REAL | REAL | REAL | REAL | REAL |
| Date/time | REAL | REAL | REAL | Date/time |
Handling blanks, empty strings, and zero values
In DAX, a null, blank value, empty cell, or a missing value are all represented by the same new value type, a BLANK. You can also generate blanks by using the BLANK function, or test for blanks by using the ISBLANK function.
How blanks are handled in operations, such as addition or concatenation, depends on the individual function. The following table summarizes the differences between DAX and Microsoft Excel formulas, in the way that blanks are handled.
| Expression | DAX | Excel |
| BLANK + BLANK | BLANK | 0 (zero) |
| BLANK +5 | 5 | 5 |
| BLANK * 5 | BLANK | 0 (zero) |
| 5/BLANK | Infinity | Error |
| 0/BLANK | NaN | Error |
| BLANK/BLANK | BLANK | Error |
| FALSE OR BLANK | FALSE | FALSE |
| FALSE AND BLANK | FALSE | FALSE |
| TRUE OR BLANK | TRUE | TRUE |
| TRUE AND BLANK | FALSE | TRUE |
| BLANK OR BLANK | BLANK | Error |
| BLANK AND BLANK | BLANK | Error |
For details on how a particular function or operator handles blanks, see the individual topics for each DAX function, in the section, DAX Function Reference.
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