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Answer: Implement a 'Custom Event' trigger that reacts to specific events from the source system to initiate the pipeline run.
Option B is the correct approach as it uses a 'Custom Event' trigger that reacts to specific events from the source system, ensuring timely processing of data changes. This strategy is more efficient than frequently polling the source system (Option A) or using a long interval (Option C), which may result in delayed processing. Option D is not suitable as it requires manual intervention and does not provide an automated solution for handling data changes.
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You are responsible for designing a data pipeline that needs to handle data from a source system that has a high rate of data change. Which of the following strategies would you use to ensure efficient and timely processing of the data in Azure Data Factory?
A
Use the 'Tumbling Window' trigger with a short interval to frequently poll the source system for changes.
B
Implement a 'Custom Event' trigger that reacts to specific events from the source system to initiate the pipeline run.
C
Use the 'Tumbling Window' trigger with a long interval to reduce the frequency of polling the source system.
D
Disable the trigger mechanism and manually initiate the pipeline run whenever needed.
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