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PL-300 · Question #361

You have a CSV file that contains user complaints. The file contains a column named Logged. Logged contains the date and time each complaint occurred. The data in Logged is in the following format: 20

The correct answer is C. Split the Logged column by using at as the delimiter.. To analyze complaints by logged date using a built-in date hierarchy, the date part must first be isolated from the original text format.

Submitted by yasin.bd· Apr 18, 2026

Question

You have a CSV file that contains user complaints. The file contains a column named Logged. Logged contains the date and time each complaint occurred. The data in Logged is in the following format: 2018-12-31 at 08:59. You need to be able to analyze the complaints by the logged date and use a built-in date hierarchy. What should you do?

Options

  • AApply a transformation to extract the last 11 characters of the Logged column and set the data
  • BChange the data type of the Logged column to Date.
  • CSplit the Logged column by using at as the delimiter.
  • DApply the Parse function from the Date transformations options to the Logged column.

How the community answered

(64 responses)
  • A
    11% (7)
  • B
    3% (2)
  • C
    81% (52)
  • D
    5% (3)

Why each option

To analyze complaints by logged date using a built-in date hierarchy, the date part must first be isolated from the original text format.

AApply a transformation to extract the last 11 characters of the Logged column and set the data

Extracting the last 11 characters would result in ' at 08:59', which is not a valid date format and cannot be converted to a Date data type.

BChange the data type of the Logged column to Date.

Directly changing the data type to Date would fail because the ' at ' string prevents Power BI from recognizing the full string as a standard date format.

CSplit the Logged column by using at as the delimiter.Correct

Splitting the 'Logged' column by the ' at ' delimiter will separate the date string (e.g., '2018-12-31') from the time string, allowing the resulting date column to be correctly identified as a Date data type and thus enabling Power BI's built-in date hierarchy.

DApply the Parse function from the Date transformations options to the Logged column.

While the Parse function can handle various date formats, '2018-12-31 at 08:59' is not a standard format that Power Query's built-in parsing would readily interpret as a date without prior text manipulation.

Concept tested: Data transformation for date parsing

Source: https://learn.microsoft.com/en-us/power-query/split-columns

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