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?
To analyze complaints by date and use a built-in date hierarchy, the most straightforward approach is to change the data type of the Logged column to Date. This will convert the string dates in the format '2018-12-31 at 08:59' to a date data type that can be easily analyzed using date functions and hierarchies in most data analysis tools.
A: cause error. C: correct, although it lacks step change data type
Change Data Type step is not required since the data type gets updated automatically after splitting the column by delimiter
Yep, the answer is C and using delimiter "at" is the easiest path and will automatically adjust the column to date format upon hitting Ok. Also, this method retains the time column in time format. If time was not a requirement, then you might be better using Extract Table Using Examples to minimize the data imported.
Datatype is changed automatically you need not do it manually :)
Question appears multiple times with different answer options, in this set of answers, C is correct.
Same question with #10, Topic 1. So the answer should be same which is C.
I tried. D is correct. It is easy to create a new column only contains the date with Examples
D adds another column, C does not
C divise la colonne en 2 donc il y a bien une nouvelle colonne
Was at the exam on February 12th 2024
Tested in PBI with dummy data : A & B will cause an error in the data --> you will read "error" instead of original data D will truncate the date correctly but will keep the original string format (no hierarchy possible) C will split correctly and apply correct format on the fly, date for date and time for time
There is another question verbatim like this one and the answer is, "extract the first 11 characters." Delimiter answer appears on both. Is it saying that extracting the characters is a better option if available? I don't understand.
C is correct. By splitting the Logged column, you can separate the date and time into two columns.
https://learn.microsoft.com/en-us/power-bi/create-reports/desktop-add-column-from-example
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.
Have you even tried? The space before 'at' will be removed automatically, that's the beauty of intelligence in Power BI. I've tried, both C and D options work. But for option D, the data type will be set to text and we need to add additional step to change data type, wherein for option C, Power BI automatically recognizes and changes the data type.
ANS. C I tested D and it didn't change the data type to Date, it remained as text. I also tested C without using spaces before and after the 'at' and it DID change the data type to date. The fact that there are two questions like this but C is common to both questions makes extra sure it is correct. C!
Microsoft Fabric said choice D.
be careful, this is the same question #10, and in 10 the right answer was D and here C. crazy
They've got different answers - In #10, D is the simplest, in this Q, C is
C for me
C is the more reliable option
Tested. Data type as Date is set auto BUT Create by example - data type is not set to Date.
correct answer