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Microsoft

DP-500 · Question #116

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 A. Yes. Removing high-cardinality unique identifier columns, such as IoT GUID or IoT ID, that are not necessary for the required time-based analysis, improves dataset performance.

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 section, 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. [Image: Table showing IoT GUID, IoT DateTime, IoT ID columns with sample data] 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 GUID column and retain the IoT ID column. Does this meet the goal?

Exhibit

DP-500 question #116 exhibit

Options

  • AYes
  • BNo

How the community answered

(52 responses)
  • A
    75% (39)
  • B
    25% (13)

Why each option

Removing high-cardinality unique identifier columns, such as IoT GUID or IoT ID, that are not necessary for the required time-based analysis, improves dataset performance.

AYesCorrect

High-cardinality unique identifier columns like IoT GUID and IoT ID consume significant memory in a Power BI dataset and negatively impact performance and compression. Since the analysis requires only 'hour' and 'day of the year' from the IoT DateTime column, removing these unneeded unique ID columns will effectively reduce dataset size and improve performance without affecting the required analysis.

BNo

Removing unique identifier columns that are not used for analysis is a common optimization technique in Power BI to reduce model size and improve query performance, thus stating 'No' would be incorrect.

Concept tested: Power Query data profiling and performance optimization

Source: https://learn.microsoft.com/en-us/power-bi/transform-model/desktop-profiling-data

Topics

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

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