PL-300 · Question #223
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 m the following format…
The correct answer is B. Create a column by example that starts with 2018-12-31 and set the data type of the new column. The Logged column contains values like '2018-12-31 at 08:59', which is a non-standard format that Power BI cannot automatically parse as a Date type. The correct approach is to use 'Column by Example' in Power Query to extract just the date portion (e.g., '2018-12-31'), and…
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 m 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
- ACreate a column by example that starts with 2018-12-31.
- BCreate a column by example that starts with 2018-12-31 and set the data type of the new column
- CApply the parse function from the Date transformations options to the Logged column.
- DAdd a conditional column that outputs 2018 if the Logged column starts with 2018 and set the
How the community answered
(25 responses)- A12% (3)
- B76% (19)
- C4% (1)
- D8% (2)
Explanation
The Logged column contains values like '2018-12-31 at 08:59', which is a non-standard format that Power BI cannot automatically parse as a Date type. The correct approach is to use 'Column by Example' in Power Query to extract just the date portion (e.g., '2018-12-31'), and then explicitly set the data type of the new column to Date. Setting the data type to Date is critical - it is what triggers Power BI to create the built-in date hierarchy (Year > Quarter > Month > Day). Option A omits the data type change, so the hierarchy would not be created. Option C (Apply Parse) would fail because the format is non-standard.
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