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Microsoft

DP-500 · Question #121

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might…

The correct answer is B. No. Moving datasets to a larger capacity may only temporarily alleviate resource constraints without addressing underlying inefficiencies or poor design that cause excessive CPU and memory consumption.

Implement and manage a data analytics environment

Question

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a Power BI Premium capacity. From the Power BI Premium Capacity Metrics app, you discover the following: - There is insufficient CPU to execute dataset refreshes. - Out-of-memory throttling occurs when the dataset is waiting. You need to recommend a solution to resolve the performance issues. Solution: You move the datasets to a larger capacity. Does this meet the goal?

Options

  • AYes
  • BNo

How the community answered

(26 responses)
  • A
    42% (11)
  • B
    58% (15)

Why each option

Moving datasets to a larger capacity may only temporarily alleviate resource constraints without addressing underlying inefficiencies or poor design that cause excessive CPU and memory consumption.

AYes

Simply increasing capacity might temporarily address resource shortages, but without optimizing the datasets themselves, the increased resources could also become saturated over time, making it an incomplete or unsustainable solution.

BNoCorrect

While moving datasets to a larger capacity provides more resources, it does not fundamentally resolve performance issues stemming from inefficient dataset design, unoptimized queries, or poorly configured refreshes. These underlying issues may eventually lead to the same resource bottlenecks in the larger capacity, thus it is not a complete or sustainable solution.

Concept tested: Power BI Premium capacity optimization vs. scaling

Source: https://learn.microsoft.com/en-us/power-bi/enterprise/service-premium-capacity-management

Topics

#Power BI Premium#Capacity Management#Performance Optimization#Dataset Refresh

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