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In your batch processing solution, you need to configure exception handling to ensure that any errors during the data processing do not cause the entire pipeline to fail. How would you implement this functionality?
A
Use Azure Data Factory's error handling capabilities to catch and log errors, and continue the pipeline execution.
B
Use Azure Databricks' exception handling mechanisms, such as try-catch blocks, to handle errors during data processing.
C
Use Azure Stream Analytics' error handling features to catch and handle errors during data processing.
D
Use Azure Functions' error handling capabilities to catch and log errors, and retry the failed operations.
