Exam PL-300 topic 1 question 10 discussion

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.

Tested. Yes, delimiter can customized by delimiting "at" but the column format is still Text. answer A automatically change the column format to Date hierarchy.

Option D

CCCCCCCCCCCCCCCCC! No Brainer!

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

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

correct is C

While Option C (splitting by "at") could work, Option D is the better answer because it provides a more direct and efficient method to extract the date. It avoids the extra step of splitting and discarding the time part, which is unnecessary when you only need the date for analysis.

Splitting the column with the custom delimiter - at works well as the datatype is automatically recognized as Date

there is no need for the time, only for the date

According to me c is correcct because D option will capture space in the 11th character and there should not be space in date.

Answer: D. Apply a transformation to extract the first 11 characters of the Logged column. Reason: The date part of the Logged column is contained in the first 11 characters ("2018-12-31"). To analyze the complaints by date and use the built-in date hierarchy in Power BI, you need to isolate the date from the time. By extracting the first 11 characters, you capture just the date part, which can then be converted to a Date data type. This allows Power BI to recognize it as a date and automatically generate a date hierarchy for analysis. Option A (extracting the last 11 characters) would give you only the time, not the date. Option B would not work directly because the column has both date and time, and the format includes additional text ("at"). Option C (splitting the column) is more complex and unnecessary when extracting the first 11 characters achieves the goal efficiently.

If you get the first 11 characters then there should be a space and you need a trim operation before transform as date. The best option is to use " at" as delimiter (also in this case notice the space). So, C. Split the Logged column by using at as the delimiter is correct

C and D both correct answers to extract the date, but after reading the question several times, in no case they mentioned the need of the time to proceed the analysis. So as an optimized solution i go with tranformation of the current column because i don't want an unused column (time) to be loaded in my model.

Technically, this is the wrong answer. If you select answer C, you will split the data by "at", but you must also convert the date into a date format to use the hierarchy. As mentioned in option A, using 11 characters to split the data might not work in case there is extra space in some of the rows. So, the right answer should be to extract the date using "at" as a custom delimiter to split the columns, then convert the split column to the date data type, and then use this column for visualization.

you should split the logged column.