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Tests whether a set of values is not valid for a specified data type.

For a tested value, this function returns true or false .
Inputs can be literal values or column references.

You can define a conditional test in a single step for valid values. See IFMISMATCHED Function.

NOTE: This function is similar to the ISVALID function, which tests for validity against a specified data type. However, unlike the ISVALID function, the ISMISMATCHED function also matches against missing values. See VALID Function.

Column reference example:

ismismatched(Qty, 'Integer') || (Qty < 0)

Output: Returns true when the value in the Qty column does not contain a valid Integer and the value is less than zero.

Numeric literal example:

ismismatched('ZZ', 'State')

Output: Returns true, since the value ZZ is not a valid U.S. State code.

ismismatched(column_string,datatype_literal)

Argument	Required?	Data Type	Description
column_string	Y	string	Name of column or string literal to be applied to the function
datatype_literal	Y	string	String literal that identifies the data type against which to validate the source values

column_string

Name of the column or string literal to be evaluated for mismatches against the specified type.

Missing literals or column values generate missing string results.
- Constants must be quoted ('Hello, World').
Multiple columns and wildcards are not supported.

Required?	Data Type	Example Value
Yes	String literal or column reference	`myColumn`

datatype_literal

Literal value for data type to which to validate the source column or string.

Column references are not supported.

Required?	Data Type	Example Value
Yes	String literal	`'Integer'`

Valid data type strings:

column_string

datatype_literal

Example - Type check functions