Last Updated: January 14, 2022

If there is an error in your calculated field’s formula, you’ll see a warning message like WHEN conditions must compare a dimension or metric with a literal value and you won’t be able to save the field: 

When this happens it means your formula has been rejected by Data Studio.

If you are new to using calculated fields, you will often see yourself in a situation where your formula has been rejected by the Data Studio. 

The most common reasons why your formula is rejected by Data Studio:

#1 You used an invalid field name

If your field name is valid, it will appear as a green or blue chip in the formula: 

However, if your field name is not valid, it will not appear as a green or blue chip in the formula.

If you reference a field that does not exist in your data source then it is going to be an invalid field. 

Similarly, if your field has got a spelling mistake or some special character (like white space) in it then it is going to be invalid.

And when Data Studio encounters an invalid field in a formula it rejects the formula. 

For example in the screenshot below, Data Studio does not recognize ‘Sales’ as a valid field and that’s why you see the error message ‘Unknow dimension or metric id: Sales‘:

#2 You used an invalid function name 

If your function name is valid, it will automatically appear as an uppercase green text: 

A function that is not spelt correctly or which is not supported by Data Studio is an example of an invalid function.

For example, in the screenshot below the function ‘concatenate’ is not a valid function name:

Therefore it is rejected by Data Studio and you see the error message ‘Unsupported operator: CONCATENATE”.

However, the function ‘CONCAT‘ is valid and that’s why it appears as an uppercase green text:

#3 Missing quotes

Make sure all literal strings are properly quoted with single or double-quotes.

For example, in the formula below the string ‘yes’ is not surrounded by a single or double quote and because of that reason, Data Studio rejected the formula and you see the error message: ‘Invalid formula: Invalid input expression – Invalid filter argument‘:

When the string ‘yes’ is surrounded by a single quote, the formula becomes valid:

#4 Mismatched parentheses

When nesting functions, it is quite easy to miss a closing parenthesis. You need to make sure that you have the same number of opening parentheses as closing parentheses.

For example, in the formula below we are nesting the ‘CONCAT’ function:

However, since the number of opening parentheses is not the same as the closing parentheses, Data Studio rejected the formula and you see the error message: Syntax error: Expected “)”.

The formula below contains the same number of opening parentheses as closing parentheses and is therefore valid:

#5 Not using the correct parameters for your function can cause your formula to be rejected by Data Studio.

#6 Applying an aggregation function on already aggregated data

For example, the ‘Sessions’ metric is already summed in Google Analytics. 

So the formula SUM(Sessions) will be rejected by Data Studio and you will see the error message ‘Re-aggregating metrics is not supported‘:

Another example:

#7 Mixing dimensions and metrics in function arguments 

An expression can have either metrics or dimensions, but not both.

For example, the formula below is made up of an expression that contains both dimension (the field ‘medium’) and metric (the field ‘Sessions’) and because of that reason, Data Studio rejected the formula and you see the error message: ‘Sorry Calculated fields can’t mix metrics (aggregated values) and dimensions (non-aggregated values). Please check the aggregation types of the fields in this formula.‘:

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