Azure Data Factory Mapping Data Flows public preview adds parameter support
Updated: 04 July, 2019
The Azure Data Factory team has added parameter support to the Mapping Data Flows public preview feature that will now allow you to build configurable data transformation logic in a code-free design environment. So, if your requirements involve logic that is based on frequently changing attributes like time, date, location, price, cost, etc., it is easy to design transformation logic once and parameterize those values inside of your Data Flows.
Details of using parameters in Data Flows can be found here. Get started using parameters in mapping data flows by clicking on the Parameters tab inside of the data flow designer or inside of your transformation expressions. This is where you will be able to create and manage your parameters which can be accessed inside of your data flow logic.
Now, when you add your data flow to an ADF pipeline, you can set the values that you wish to pass to your data flow by using pipeline expressions, static values, or use Data Flow expressions. The ADF pipeline expression language supported in pipeline parameters is documented here and the Data Flow Expression Language is documented here.
Setting these parameters from your pipeline will execute your data flow with these immutable values, dynamically changing the values inside of your data flow upon every execution. You can use the parameter values inside of Source and Sink transformation settings or inside of your transformation expressions.