In Data Factory, what is the difference between Conditional Split and Assert? When to use what?

Partha Das 276 Reputation points


In Data Factory, what is the difference between Conditional Split and Assert? When to use what? If you can provide some use cases for that decision making.

Azure Data Factory
Azure Data Factory
An Azure service for ingesting, preparing, and transforming data at scale.
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  1. MarkKromer-MSFT 5,176 Reputation points Microsoft Employee

    Conditional split is really just a case / switch / if-then-else construct whereas Assert is for data quality rules, with the built-in capability to set expectations, set quality rules, and set rows as error rows.

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  2. ShaktiSingh-MSFT 11,136 Reputation points Microsoft Employee

    Hi @Partha Das ,

    Thanks for posting this question in Microsoft Q&A platform.

    In addition to @MarkKromer-MSFT 's reply, you may refer to the official Microsoft documentation page for Conditional Split and Assert transformations as well as the videos demonstrating the same as below:

    Assert in Data Flow

    Conditional Split in Data Flow

    Hope this will help. Please let us know if any further queries.


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  3. ShaikMaheer-MSFT 35,796 Reputation points Microsoft Employee

    Hi @Partha Das ,

    Conditional split transformation can be used when you want to split incoming rows as separate streams based on conditions and process them accordingly. Whereas Assert Transformation can be used when you want to perform data validation on the incoming rows.

    Let's assume you have employee data coming in with different department Ids and want to split those rows based on departments and process each department related rows separately and load them into different tables. In this case you can use conditional split transformation. Please check below video where with an example I explained about conditional split transformation.
    Conditional Split Transformation in Mapping Data Flow in Azure data factory

    Let's assume if you want to validate incoming rows and check for data quality you can consider using assert transformation. In below video, I explain usage of assert transformation with some examples for better understanding. Kindly check same.
    Assert Transformation in Mapping Data Flows in Azure Data Factory

    Hope this helps. Please let me know if any further queries.


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