Answer C is best approach Split the Logged column by using "at" as the delimiter.

C, You should split the Logged column by using "at" as the delimiter. This will allow you to separate the date and time into separate columns, which will enable you to analyze the complaints by date and use a built-in date hierarchy. Alternatively, you could also use a transformation to extract the date and time from the Logged column and set the data type of the new columns to Date and Time, respectively. Option A is incorrect because it only extracts the last 11 characters of the Logged column, which would not include the date. Option B is incorrect because the data in the Logged column is in a non-standard date format and cannot be directly converted to the Date data type. Option D is incorrect because it only extracts the first 11 characters of the Logged column, which would not include the time.

we can split 2018-12-31 at 08:59. using Space (" ") as delimiter and then will remove column where "at" is present.

The correct answer is definitely C. In the power query editor, you can customized split it by 'at'. Once you do it, it would result in giving you two column, one of them containing the date with the date datatype, and the other containing time with the time datatype. Once you apply and close it, in the power bi report, you can see that you have a date hierarchy.

Wouldn't it be the first 10 characters you would want to extract? I believe D works, but you would need the additional step of changing the data type to Date, since you will be using a hierarchy.

B should be the answer, "analyze the complaints by the logged date".

B should be the answer

I checked both C and D work. Delimiter should be custom and " at " with spaces before and after. As D is faster and you do not need time column, this is probably the correct answer.

Answer D is Correct. Since he is asking to extract only the date from that column, using "at" as a delimiter to split would separate the date and time into two different columns. This could result in unnecessary memory usage for the report.

c is the correct answer

BE CAREFULL, QUESTION 10 AND 27ARE EXACTLY THE SAME, here the answer is D, but in 27 is C. incredible

there are two major issues with both C and D C have the wrong delimeter. "at" needs you to have a trim operation after the split. " at " (with a space before and after) will do the trick for us D we cannot be sure that different dates with month or days with just one units will be written as i.e. 2024-12-03 or 2024-12-3 making the fixed value of 11 character a bit confusing. mostly in dates like 2024-1-1 at 00:00:0000 where the first 11 characters are 2024-1-1 a i think that C will be better. in both cases the resulted columns need to have other transformation to be interpreted as date and not string

This Question appeared in the Mock Exam provided in Coursera Power BI course and has B. Change the data type of the Logged column to Date as the correct answer. Even though I think it should be "C"

C is the correct option because when i did it practically splitting on the basis of "at" would make it 2 columns the date column would automatically have date datatype and other time column will have time datatype and that to automatically This would preserve our data and will not lead to dataloss as well hence C is the correct option in my opinion

answer is D, apply a TRANSFORMATION; using a demo. create a csv with complaint id, complaint date(use the date format described in the example) Create new report -> transform data : opens Power Query editor New Sources -> csv Here comes the tricky part: when you import a csv, you can apply TRANSFORMATION on the fly; there is a button at the bottom left part of the window : Extract table using examples click that button, here comes the TRANSFORMATION You are presented with a form allowing you to pick up the fields and the data you want by example. Name your headers according to the csv headers and in the first data row, type the kind of data you want. For the logged column, you will type the date only. After import you will see that Query editor imported and converted your field in Date format. Finally, go to report view and expand your imported csv in the Data pane. You will see that Power BI created a date hierarchy

I tried in my power bi editor and when I extract first 11 or 10 characters the datatype still in string format, but when I split with "at" the data type automatically changed to date and time So C is my choice

This thing! It was at the exam today on February 12th 2024, question is annoying