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Microsoft

DP-500 · Question #87

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. The solution only removes the IoT ID column but retains the IoT GUID column, which is still unique per row and fails to improve dataset performance or enable hour/day analysis.

Query and transform data

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 question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. From Power Query Editor, you profile the data shown in the following exhibit. The IoT GUID and IoT ID columns are unique to each row in the query. You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance. Solution: You remove the IoT ID column and retain the IoT GUID column. Does this meet the goal?

Options

  • AYes
  • BNo

How the community answered

(21 responses)
  • A
    19% (4)
  • B
    81% (17)

Why each option

The solution only removes the IoT ID column but retains the IoT GUID column, which is still unique per row and fails to improve dataset performance or enable hour/day analysis.

AYes

Keeping the IoT GUID column does not reduce cardinality or enable time-based analysis by hour and day, so the performance and analytical goals are not met.

BNoCorrect

Retaining the IoT GUID column, which is also unique per row, still introduces high cardinality that harms dataset performance. Furthermore, neither IoT column provides hour or day granularity - time-based columns would need to be derived or retained separately to support analysis by hour and day of the year. Both unique-identifier columns should be removed to achieve the performance goal.

Concept tested: Power Query data profiling and dataset performance optimization

Source: https://learn.microsoft.com/en-us/power-bi/guidance/import-modeling-data-reduction

Topics

#Power Query Editor#Data Transformation#Performance Optimization#Column Management

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