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Answer: Analyze the relationships between tables and remove any unnecessary or redundant relationships to streamline data processing.
Option A is the most effective initial step for optimizing a semantic model because it directly addresses the foundational structure of the model by simplifying relationships, which can significantly reduce unnecessary data processing and improve overall performance. While refactoring calculations (Option B) and adding indexes (Option C) can contribute to performance improvements, they are secondary to ensuring the model's relationships are optimized. Upgrading hardware resources (Option D) may offer a temporary solution but does not address the root cause of performance issues within the semantic model itself. Therefore, analyzing and optimizing table relationships is the most strategic approach to enhancing model performance.
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with optimizing a semantic model in Tabular Editor 2 to enhance performance. The model comprises multiple tables with intricate relationships and complex calculations. Considering the constraints of cost, compliance, and scalability, which of the following steps should you prioritize to optimize the semantic model effectively? Choose the best option from the four provided.
A
Analyze the relationships between tables and remove any unnecessary or redundant relationships to streamline data processing.
B
Refactor the calculations within the model to utilize more efficient DAX expressions and functions, ensuring calculations are as lean as possible.
C
Implement additional indexes on the tables to accelerate query execution times, focusing on tables with the highest query loads.
D
Upgrade the hardware resources allocated to the semantic model processing engine to accommodate larger datasets and complex calculations more efficiently.