Stringify transformation in mapping data flow

APPLIES TO: Azure Data Factory Azure Synapse Analytics


Try out Data Factory in Microsoft Fabric, an all-in-one analytics solution for enterprises. Microsoft Fabric covers everything from data movement to data science, real-time analytics, business intelligence, and reporting. Learn how to start a new trial for free!

Use the stringify transformation to turn complex data types into strings. This can be useful when you need to store or send column data as a single string entity that may originate as a structure, map, or array type.


In the stringify transformation configuration panel, you'll first pick the type of data contained in the columns that you wish to parse inline. The stringify transformation also contains the following configuration settings.

Stringify settings


Similar to derived columns and aggregates, this is where you'll either modify an exiting column by selecting it from the drop-down picker. Or you can type in the name of a new column here. ADF will store the stringifies source data in this column. In most cases, you'll want to define a new column that stringifies the incoming complex field type.


Use the expression builder to set the source complex field that is to be stringified. This can be as simple as just selecting the source column with the self-contained data that you wish to stringify, or you can create complex expressions to parse.

Stringify expressions

Example expression

In this example, is an array inside a structure returned from a REST source.

Data flow script

stringify(mydata = ? string,
	format: 'json') ~> Stringify1