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Answer: Data read and write throughput in Azure Blob Storage and Azure SQL Database.
To measure the performance of data movement in a data pipeline, you should monitor the data read and write throughput in both the source (Azure Blob Storage) and the destination (Azure SQL Database). This will give you insights into the speed at which data is being moved and help identify any bottlenecks or performance issues. Option B is related to the execution of data factory pipelines and activities, but it does not directly measure the performance of data movement. Option C is related to the performance of the Azure Data Factory service itself, not the data movement. Option D is related to the triggers and their execution status, which is not directly related to the performance of data movement.
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You are responsible for monitoring the performance of data movement in a data pipeline that uses Azure Data Factory to copy data from Azure Blob Storage to Azure SQL Database. Which of the following metrics should you monitor to measure the performance of data movement?
A
Data read and write throughput in Azure Blob Storage and Azure SQL Database.
B
Number of data factory pipelines and activities executed.
C
CPU and memory usage of the Azure Data Factory service.
D
Number of data factory triggers and their execution status.