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Answer: Adjust the Fabric environment's configuration settings, including memory allocation and query execution options, to better match the current workload demands and anticipated growth, ensuring optimal resource utilization.
Option D is the correct answer because it directly addresses the need for optimizing the Fabric environment's performance and scalability by adjusting configuration settings to match workload demands. This approach is cost-effective, complies with data governance policies by not requiring changes to data models or pipelines, and can be implemented with minimal downtime. Options A, B, and C, while beneficial, do not provide as comprehensive a solution as Option D. Option A focuses on data partitioning and indexing, which may improve query performance but does not address system-wide resource utilization. Option B is about monitoring, which is crucial for identifying issues but does not solve them. Option C involves optimizing data pipelines, which may reduce some load but does not directly improve the Fabric environment's configuration for better performance and scalability.
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with optimizing the performance of a Fabric environment that supports a large organization with complex data models and a high volume of users. The organization is experiencing slow query responses and system bottlenecks during peak usage times. You need to recommend a solution that not only addresses the immediate performance issues but also ensures scalability for future growth. Consider the following constraints: the solution must be cost-effective, comply with organizational data governance policies, and minimize downtime during implementation. Which of the following actions would you recommend as the BEST solution to optimize the Fabric environment's performance and scalability? (Choose one option.)
A
Implement data partitioning and indexing strategies across all data models to enhance query performance, ensuring that the strategies are aligned with the most frequently accessed data patterns.
B
Deploy Azure Monitor and Azure Application Insights to continuously monitor the Fabric environment's performance, setting up alerts for any performance degradation or bottlenecks.
C
Utilize Azure Data Factory to redesign and optimize all data pipelines, focusing on reducing data movement and transformation times to alleviate the load on the Fabric environment.
D
Adjust the Fabric environment's configuration settings, including memory allocation and query execution options, to better match the current workload demands and anticipated growth, ensuring optimal resource utilization.