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Answer: Add each component as a separate activity within the data pipeline to allow for independent execution, proper sequencing, and easier troubleshooting.
The optimal approach is to add each component as a separate activity within the data pipeline. This design allows for independent execution of stored procedures, notebooks, and dataflows in the correct sequence, ensuring data integrity and processing efficiency. It also facilitates easier troubleshooting and maintenance, as each component's execution can be monitored and managed individually. Combining components into a single activity or using a dataflow to execute others may lead to complexities in sequencing and error handling, while scheduling components to run separately and merging results manually introduces unnecessary overhead and potential for errors.
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As a Microsoft Fabric Analytics Engineer Associate, you are designing a data pipeline that integrates stored procedures, notebooks, and dataflows to process and analyze data for a retail company. The company requires the pipeline to be cost-effective, scalable, and maintainable, with each component executing in a specific sequence to ensure data integrity. Given these requirements, which of the following approaches should you take to optimally add these components to the data pipeline? (Choose one correct option)
A
Combine all components into a single activity within the data pipeline to minimize costs and simplify management.
B
Use a dataflow activity to encapsulate the execution of stored procedures, notebooks, and other dataflows, reducing the number of activities in the pipeline.
C
Schedule each component to run independently at different times and manually merge the results in the data pipeline to avoid conflicts.
D
Add each component as a separate activity within the data pipeline to allow for independent execution, proper sequencing, and easier troubleshooting.
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