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Answer: Configure individual triggers within each component (dataflow and notebook) to specify the execution schedule, leveraging Azure's native scheduling capabilities.
Configuring individual triggers within each component to specify the execution schedule is the best approach because it leverages Azure's native scheduling capabilities, ensuring cost efficiency, scalability, and compliance with Azure's best practices. This method eliminates the need for manual intervention or reliance on external tools, providing a seamless and automated solution within the Azure ecosystem.
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with automating the execution of a dataflow and a notebook within a specific Azure environment to ensure data is processed and analyzed at regular intervals without manual intervention. The solution must adhere to Azure's best practices for cost efficiency, scalability, and compliance with internal data governance policies. Given these requirements, which of the following approaches is the BEST to schedule these components? (Choose one correct option)
A
Configure individual triggers within each component (dataflow and notebook) to specify the execution schedule, leveraging Azure's native scheduling capabilities.
B
Assign a team member to manually execute the dataflow and notebook at the predetermined intervals, ensuring adherence to the schedule.
C
Develop a custom data pipeline that orchestrates the execution of both the dataflow and notebook, incorporating Azure Data Factory for scheduling and monitoring.
D
Integrate a third-party scheduling tool external to Azure to manage the execution schedule of the dataflow and notebook, bypassing Azure's native features.
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