Exam PL-300 topic 1 question 27 discussion

A: cause error. C: correct, although it lacks step change data type

Question appears multiple times with different answer options, in this set of answers, C is correct.

The best answer is: D. Create a column by example that starts with 2018-12-31. Here’s why: The original format "2018-12-31 at 08:59" is not recognized as a valid date by Power BI because of the "at" text. Using Column from Examples in Power Query lets you easily extract just the date portion (2018-12-31) without writing M code. Once extracted, you can change the new column’s data type to Date, which enables Power BI’s built-in date hierarchy (Year, Quarter, Month, Day). Why not the others? A. Parse function: Power BI doesn’t have a built-in “Parse” function that can handle this custom format directly. B. Change data type to Date: This will fail because the "at" string makes the format invalid for automatic conversion. C. Split by “at”: This works, but it creates two columns and requires extra cleanup. Option D is more efficient and intuitive.

Artificial intelligence (Gemini) answer: The most effective solution to analyze complaints by the logged date and use a built-in date hierarchy in Power BI, given the "2018-12-31 at 08:59" format, is to change the data type of the Logged column to Date. Here's why: * Power BI's Intelligent Handling: Power BI is very good at recognizing common date and time formats.

Column By Example i.e, Answer D is correct, since it automatically extracts the date from the column and changes its type to DATE in the new column. Again, using 'at' as delimiter will introduce spaces as prefix and suffix and create an unneeded time column which is not asked for in the question

I had a similar question in the Microsoft pl-300 preparation Course (on coursera): " You have a CSV file that contains user complaints. The table contains a column called Logged, which has data and the time of each complaint. The data is logged in the following format: 2022-12-21 at 08:35. You want to analyze the complaints by the logged date and utilize Power BI’s built-in date hierarchy. What should you do? - Split the logged column using ‘at’ as a delimiter. ✖ - You can use the same column as the date hierarchy. ✖ - Apply transformation to extract the column's first characters that only contain the date. ✖ - Change the data type of the logged column to Date. ✔ " So answer is B, Probably because PowerBI can recognize Date in that format

If we create a column with date format. Power bi will automatically identify it as date column

DataType change is direct and allows to analyze by date, month, year etc. No need to split and analyze.

C work faster then D becouse automaticcally reconize the data type for date and time. D require an additional step to change data type from text and in both case you will have 2 column as final result.

I want to say the answer is D because the question talks about a built in date hierarchy

D. Create a column by example that starts with 2018-12-31 is the correct answer bcz if you add column from example(i.e. 2018-12-31) then it gives only data format. Answer C is wrong bcz if we use "at as delimiter then the space before at will be added in the data format so the column will not automatically detect as a date format.

This is similar to another question in which "C - Split the Logged column by using at as the delimiter" was the right answer. But why in this case "D. Create a column by example that starts with 2018-12-31" is wrong???

correct answer

Tested. Data type as Date is set auto BUT Create by example - data type is not set to Date.

C is the more reliable option

C for me

Microsoft Fabric said choice D.