PL-300 · Question #299
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…
The correct answer is C. Split the Logged column by using at as the delimiter. The value '2018-12-31 at 08:59' is not a standard date/time format that Power BI can automatically parse, so simply changing the data type (Option B) would produce errors. Splitting the column by the delimiter 'at' produces two new columns: '2018-12-31 ' (the date part) 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 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 a transformation to extract the first 11 characters of the Logged column.
How the community answered
(55 responses)- A4% (2)
- B4% (2)
- C84% (46)
- D9% (5)
Explanation
The value '2018-12-31 at 08:59' is not a standard date/time format that Power BI can automatically parse, so simply changing the data type (Option B) would produce errors. Splitting the column by the delimiter 'at' produces two new columns: '2018-12-31 ' (the date part) and ' 08:59' (the time part). You then change the first column's data type to Date, which enables Power BI's built-in date hierarchy (Year > Quarter > Month > Day). Option D (extract first 11 characters) gets the date string but leaves it as text, still requiring a data type change and producing a less clean result than splitting.
Community Discussion
No community discussion yet for this question.