In Mapping Data Flow, which transformation routes data rows to different streams based on matching conditions?

The Conditional Split transformation is designed to direct data rows into different streams based on specified conditions or criteria. It enables users to define one or multiple conditions, allowing the data flow to evaluate each row and determine which condition it meets. Once the row meets a condition, it is routed to the corresponding output stream associated with that condition.

This capability is particularly useful for scenarios where you need to segment data for various downstream analyses or processing. For example, you might want to separate rows of data that meet certain criteria, such as filtering customers by location or products by category, and then process each subset of data differently.

In contrast, the Lookup transformation is used to reference a dataset to enrich or validate data but doesn't route data into different streams. Data Conversion is meant for changing the data types of columns, whereas the Aggregate transformation focuses on summarizing data rather than directing it to different paths. Thus, the Conditional Split transformation uniquely fulfills the requirement of routing data based on matching conditions.