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List Rows Output on Dataverse Table is Omitting Columns that are null

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Posted on by kyasprin

When I use List Rows on a Dataverse Table, the output json does not show columns with null values. This is a big problem when needing to parse json which requires entering the schema that contains both columns, but the output doesn't match the schema causing action to fail b/c a column was null and omitted instead of showing a blank/null value.

Example:

I have a Dataverse table called 'OmittedNullColumn' with fields for Name and Location. There are 3 records, 1 has both Name and Location, the other 2 only have either a Name or a Location, but not the other. When you run list rows on this table, the response is the 3 records, but the 2 items with Null values don't contain those fields. The expectation is cr71c_name and cr71c_location in both of these situations should show those columns exist but have no value, null value, etc.

I tried adding these columns in the List Rows Select Columns and in Filter Rows hoping maybe directly referencing them might force those null columns to appear in the JSON output, but no luck

Is there a way to force power automate, list rows, or Dataverse (where ever the issue is here) to display the columns in the json output with no value instead of omitting the entry entirely?

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Chriddle 8,441 Super User 2025 Season 2 on at

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Check the Parse JSON's schema and remove the property names from the "required" array.

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kyasprin 41 on at

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I marked the 'remove columns from JSON Parse' as solution as this fixed our issues, but wanted to give some extra context and things to try for others who may see this where removing the columns from Parse JSON may not resolve their issue.

As mentioned in accepted solution, you can remove any columns that could be null:

Looks like you can also changed the "required" section text in the schema to "optional" or delete the entire "required" section altogether so all columns are optional (unsure if this could have other ramifications if no columns are required in some situations.

Something else I saw recommended that didn't work for my use case but may be useful, you can include the ability within each column for the values to be null. So in the Schema you might see something like this:

"cr71c_name": { "type": "string" }

And you can modify the "type" to include the data format (string, number, etc.) to include null like this:

"cr71c_name": { "type": [ "string", "null" ] }

If you find that you need null columns to appear in the output for some reason, you can use a 'Select' action to specify the columns you need to show:

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