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In a scenario where you are tasked with configuring error handling for a data transformation process in Azure Data Factory, what steps would you take to ensure robust error handling and logging?
A
Enable the 'Stop on data validation errors' option in the dataset settings.
B
Add a Try-Catch block in the data flow mapping to handle any transformation errors.
C
Configure the 'Log storage settings' in the pipeline to store error logs in an Azure Blob Storage account.
D
Implement a custom error handling logic in the source query of the Copy Data activity.
