Microsoft Fabric Analytics Engineer Associate DP-600
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with optimizing the refresh process for a large semantic model dataset that is updated frequently. The current full refresh process is not only time-consuming but also significantly impacts resource utilization. Your goal is to implement an incremental refresh strategy that minimizes refresh time and resource usage while ensuring data accuracy and consistency. Considering the need for scalability, cost-efficiency, and compliance with data governance policies, which of the following approaches would you choose? (Choose one)
A
Create a separate table to store only the new or updated data and refresh this table periodically. This approach requires additional storage and may introduce data synchronization challenges.
B
Modify the existing table to include a timestamp column and configure the refresh process to update only the rows with timestamps indicating changes since the last refresh. This leverages built-in functionality for efficiency and simplicity.
C
Develop a custom script to identify and refresh only the rows that have changed since the last refresh. While flexible, this approach may introduce complexity and maintenance overhead.
D
Disable the automatic refresh mechanism and manually trigger a full refresh when necessary. This approach eliminates the need for incremental logic but requires manual intervention and may not meet real-time data requirements.