PL-300 · Question #270
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. Yes, this solution meets the goal. Splitting the IoT DateTime column into separate Date and Time columns directly supports the required analyses: the Date column enables day-of-year analysis and the Time column enables hour-level analysis. Performance also improves because…
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. The IoT GUID and IoT ID columns are unique to each row in query. You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance. Solution: You split the loT DateTime column into a column named Date and a column named Time. Does this meet the goal?
Options
- AYes
- BNo
How the community answered
(68 responses)- A72% (49)
- B28% (19)
Explanation
Yes, this solution meets the goal. Splitting the IoT DateTime column into separate Date and Time columns directly supports the required analyses: the Date column enables day-of-year analysis and the Time column enables hour-level analysis. Performance also improves because VertiPaq can compress integer-like date and time columns far more efficiently than a combined datetime column, and column cardinality is reduced (a pure date has far fewer distinct values than a full datetime). Since the IoT GUID and IoT ID columns are already unique-row identifiers, splitting DateTime does not create ambiguity in the data.
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