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Answer: Analyze the partitions to identify inefficiencies and refactor them using more efficient partitioning strategies and keys, ensuring the solution is scalable and cost-effective.
Option B is the correct approach because it directly addresses the performance issues by analyzing and refactoring the partitions to use more efficient strategies and keys. This solution is scalable and cost-effective, aligning with the organization's requirements. Option A may simplify management but fails to meet scalability needs. Option C could reduce processing time but at the cost of usability. Option D does not solve the root cause of the performance issues related to partition complexity.
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with optimizing a semantic model that contains a large number of partitions. The model is experiencing performance issues due to the complexity of managing these partitions. The organization requires a solution that not only improves performance but also adheres to cost constraints and scalability requirements. Which of the following steps would you take to optimize the performance of the semantic model while considering these constraints? (Choose one option.)
A
Remove all the partitions and store the entire dataset in a single partition to simplify management, despite potential scalability issues.
B
Analyze the partitions to identify inefficiencies and refactor them using more efficient partitioning strategies and keys, ensuring the solution is scalable and cost-effective.
C
Disable the automatic processing of the partitions to reduce initial processing time, and manually process them as needed, accepting the trade-off in usability.
D
Increase the memory allocation for the semantic model processing engine to handle the complex partitions, without addressing the underlying partitioning strategy.
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