How should you complete the Data Factory data flow script?

DRAG DROP

You need to create an Azure Data Factory pipeline to process data for the following three departments at your company: Ecommerce, retail, and wholesale. The solution must ensure that data can also be processed for the entire company.

How should you complete the Data Factory data flow script? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.

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Answer:

Explanation:

The conditional split transformation routes data rows to different streams based on matching conditions. The conditional split transformation is similar to a CASE decision structure in a programming language. The transformation evaluates expressions, and based on the results, directs the data row to the specified stream.

Box 1: dept==’ecommerce’, dept==’retail’, dept==’wholesale’

First we put the condition. The order must match the stream labeling we define in Box 3.

Syntax:

<incomingStream>

split(

<conditionalExpression1>

<conditionalExpression2>

disjoint: {true | false}

) ~> <splitTx>@(stream1, stream2, …, <defaultStream>)

Box 2: discount: false

disjoint is false because the data goes to the first matching condition. All remaining rows matching the third condition go to output stream all.

Box 3: ecommerce, retail, wholesale, all

Label the streams