Data Engineering on Microsoft Azure — Question 17

You are creating an Azure Data Factory data flow that will ingest data from a CSV file, cast columns to specified types of data, and insert the data into a table in an
Azure Synapse Analytic dedicated SQL pool. The CSV file contains three columns named username, comment, and date.
The data flow already contains the following:
✑ A source transformation.
✑ A Derived Column transformation to set the appropriate types of data.
✑ A sink transformation to land the data in the pool.
You need to ensure that the data flow meets the following requirements:
✑ All valid rows must be written to the destination table.
✑ Truncation errors in the comment column must be avoided proactively.
✑ Any rows containing comment values that will cause truncation errors upon insert must be written to a file in blob storage.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer options

• A. To the data flow, add a sink transformation to write the rows to a file in blob storage.
• B. To the data flow, add a Conditional Split transformation to separate the rows that will cause truncation errors.
• C. To the data flow, add a filter transformation to filter out rows that will cause truncation errors.
• D. Add a select transformation to select only the rows that will cause truncation errors.

Correct answer: A, B

Explanation

The correct answers are A and B. Adding a sink transformation (A) allows you to write rows that could cause truncation errors to a file in blob storage. The Conditional Split transformation (B) is essential for separating the rows that will lead to truncation errors from the valid rows. Options C and D are incorrect because filtering out rows or selecting only problematic rows does not fulfill the requirement of writing those rows to a separate location.