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You are a Microsoft Fabric Analytics Engineer working on optimizing an enterprise-scale semantic model. A report you are responsible for contains a large number of visuals with complex data aggregations, leading to significant delays in loading and rendering times. The business requires the report to be both performant and to maintain all current data aggregations for decision-making purposes. Given these constraints, which of the following approaches would BEST optimize the report's performance while meeting business requirements? (Choose one option)
A
Eliminate all complex data aggregations from the report to simplify the data processing, despite the business's need for detailed aggregations.
B
Conduct a thorough analysis of the existing data aggregations to identify inefficiencies and refactor them using more optimal aggregation functions and strategies, ensuring the report meets performance and business requirements.
C
Implement a manual processing system for data aggregations, requiring users to trigger aggregation processing as needed, which may delay access to critical business insights.
D
Upgrade the hardware resources allocated to the report processing engine, without addressing the underlying inefficiencies in the data aggregations.