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.

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.
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