A transformation is a data manipulation instruction that changes the data as it moves from source to target. Transformations are part of the data flow pipeline and are typically used to do things like join, split, filter, rearrange, compare, calculate, rollup, combine or see the difference. Transformations define the functions that must be performed on the input data and the result that should be provided as output. You can use one or multiple transformations in a data flow to achieve the data manipulation required as per the business logic.

The transformations used in the data flow are converted into SQL code during runtime based on the fields and properties defined in them. You can view the script generated under the Script tab for the selected transformation. The details can be found under pages for transforms. 

You can also see the sample data generated for each transform using the interactive data flow option. For more information on this, refer Working with Interactive Data Flow.

Below are the transformations that can be used in the data flow.

Source Instance transform: For more information, refer Working with Source Instance Transform.

Target Instance transform: For more information, refer Working with Target Instance Transform.

Expression transform: For more information, refer Working with Expression Transform.

Filter transform: For more information, refer Working with Filter transform.

Joiner transform: For more information, refer Working with Joiner transform.

Rollup transform: For more information, refer Working with Rollup transform.

Splitter transform: For more information, refer Working with Splitter Transform.

Temp Stage transform: For more information, refer Working with Temp Stage Transform.

Venn Group transform: For more information, refer Working with Venn group transform.

Transpose transformFor more information, refer Working with Transpose Transform

Select transformFor more information, refer Working with Select Transform.

Datacleanse transformFor more information, refer Working with Datacleanse Transform