Exam PL-300 topic 2 question 58 discussion

Option C should be the correct answer not option B

To analyze the complaints by the logged date and use a built-in date hierarchy, we need to extract the date portion of the "Logged" column and convert it to a date format. Therefore, the best option among the given choices is: A. Apply a transformation to extract the first 11 characters of the logged column. Since the date value is stored in the first 11 characters of the "Logged" column, extracting those characters using the "Extract" transformation in Power Query will give us the date value in the format "yyyy-MM-dd". We can then set the data type of the new column to "Date" to convert it into a date format. This will allow us to analyze the complaints by the logged date and use the built-in date hierarchy in Power BI. Option B is not necessary and will not achieve the desired result. Option C will create a single date value and not allow us to analyze the complaints by the logged date. Option D suggested extracting the last 11 characters, but they contain both date and time values and may not result in the correct date format.

The Logged column has values like: 2018-12-31 at 08:59 To analyze by date using a date hierarchy (Year > Quarter > Month > Day), you need to extract just the date portion (2018-12-31) and convert it to a Date data type. The first 10 characters give you the date (2018-12-31), but the answer suggests extracting the first 11 characters, which includes a space after the date ("2018-12-31 "). This is acceptable since Power BI will ignore the extra space when converting to Date. Once extracted, you set the data type to Date, which enables built-in date hierarchy in Power BI.

This is a poor question with multiple correct answers. Specifically A and C could BOTH work. I created a CSV and tested A in PowerBI. After the split PowerBI automatically removed the trailing space and recognized the first 11 characters as a date. You should try it yourself. For answer C you could add the date column and fill with your required dates and also get a working solution. With PowerBI's automatic trailing space deletion and date detection, Answer A might be the best choice here.

C is correct

Extracting the first 11 characters ("2018-12-31") will give you the date part, which can then be converted to a Date data type. This will allow you to use the built-in Date Hierarchy in Power BI to analyze complaints by year, quarter, month, and day.

I don't know but I think we are talking about different types of “transformation” here Once by Power Query (M) (converting to date works) -> A is correct and Dax (convert to date does not work) -> A is wrong I have just tested it and I will choose A Please write if I miss something :)

A would be the better answer, You need to extract only the date portion (which is the first 11 characters: "2018-12-31") then set the data type using powerbi's out of the box date hierarcy feature. D cannot be as the "at 08:59" is outside the 11 character which cannot be converted to date.

C is right. A is wrong becouse eventually are 10 not 11 characters to extract the date B end with a whole number datat type insted of date D doesn't even extract a reconizable

Extracting "last 11 characters" as in Option D would result in uselss data (as "31 at 08:59") Extracting "first 11 characters would result in a useful date string (as "2018-12-3") but it would be still needed to change data type to "Date" (data is coming from a csv file, so definitively the original field content is not "Date" type). Conditional column based on whether a field starts with 2018 will not work... what if it's a date from different year? this also would only result year number but not entire date for 2018 dates and its type would be set to whole number not date, so date hierarchy would also not be available. Opion C is the right one in my opinion, creating a full brand column with Date type data on it based on a first example out of the first data row mentioned in the question

Option C is correct only - I created an example csv and tested it. Using this, Power BI automatically generates the hierarchy required by the question also. A is wrong because it will only partially get you there, returning the date as a String value not formatted as date. B is only going to return the Year number D is going to give you some of time, including the word 'at' etc.

I'd select option C

I am not sure also why there was a correct answer on getting first 11 characters as there are only 10, 11 will have a space and not be recognized if trying to convert to date format, however, it will never be "B", as the question is to analyse over time, not just by year. Answer "B" is just year.

Same this question came in previous topic (question #10, Topic1), and the answer was (Apply a transformation to extract the first 11 characters of the Logged column). So which one is correct?

Yes C is correct answer, B is making the date field a whole number which doesnt help in analysing the date field data

B is the correct answer , because C is making the table as Date Table, which will remove the Date hierarchy feature .Question demands Date Hierarchy

we didn't get the answer :c