Exam PL-300 topic 2 question 19 discussion

Answer is wrong, the table shouldn't be transposed, the order should be: 1. Use first row as header 2. Unpivot all columns other than "Measure" 3. Rename "Attribute" to "Year" 4. Change data type of "Year" to date (Date > Year)

To me, 1. Transpose the table 2. Use first row as headers 3. Rename the Measure column as Year 4. Change the data type of the Year column to Date. Yo don't need to unpivot but transpose because you need the measures in columns. Don't you agree?

Answer is wrong. The order should be : 1.Use the First row as Header. 2. Unpivot all the columns other than Measure. 3 Rename the Measure column as Year. 4.change the data type of the year column to date . when you use replace : When placing the first row as a header, the data type changes to numeric and changing it back to string would generate an additional step that is not contemplated in the solution.in this problem should be used unpivot. thanks.

I've created same excel table and imported into my own pbix. I've: 1.-TRANSPOSED the table, 2.- PROMOTED headers, 3.- RENAMED "measure" as "year" and, at this point I'm able to set a visual (line graph) with the three measures year over year Changing data type of {2016, 2017, 2018, 2019, 2020} column to DATE type results in ({08/07/1905, 09/07/1905, 10/07/1905, 11/07/1905, 12/07/1905}) column so, if 4 actions are required here, only other action I can select is to 4.- UNPIVOT other columns than measure. With that 4 actions I still can represent the 3 measures over all years and I guess some custom DAX calculations can be defined to get the YoY calculations

1. Transpose the table 2. Use first row as headers 3. Rename the Measure column as Year 4. Change the data type of the Year column to Date. I tested this and worked

Transpose the table Use the first row as headers Rename the Measure column as Year Change the datatype of the Year column to Date its the correct answer

Answer is correct. I just try on my computer and works perfectly.

I totally agree with ThariCD: 1 - Use the first row as headers (we now have column names) 2 - Unpivot all the columns other than Measure (we have years in one column only) 3 - Rename the Attribute column as Year (we have the year column) 4 - Change the data type of the Year column to Date (I only have a doubt for this step, why an year should be considered as a Date???)

The answer is wrong the table should not be transposed

With Transpose there is an issue to do in one step conversion of Year data type from Int to Date (it has to be done in 2 steps int->text->date) and it results in 5 steps, not 4. IDK the answer here.

• 1. Transpose the table • 2. Use first row as headers • 3. Rename the Measure column as Year • 4. Change the data type of the Year column to Date.

The given answer is correct.

Transpose Use the first rows as headers Rename the measure as year Change the data type of the year column

Sorry, but the last step is wrong, if you change the year to datatype date you would get 17th July, 1905. Actually my problem is: which 4th option do I select when all remaining options are wrong?????

The 3rd step is wrong. You do not need to unpivot. The solution must be: 1. Transpose the table 2. Use first row as headers 3. Rename the Measure column as Year 4. Change the data type of the Year column to Date. This is really a tricky questions and most of us tend to go immediately to "unpivot other columns". The key here is to check the data carefully. And if you noticed on the first column, besides the first row which is measure, the other rows are all fields as well. So transpose instead of unpivot.

TRANSPOSE the table Use first row as header Rename the measure column as Year Change the data type of the year column to Date

Tested in Power BI, Both unpivot and transpose worked. I think the answer depends on the desired format of outcome table. If you want a 3 * 15 (row * col) table, with each measure and year to be a dependent row, then unpivot. If you want a 5 * 4 (row * col) table, with measures(revenue etc.) are columns and year in the row, then transpose.