PowerBI - Part III

You have Power BI report that contains the fields shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.

• One explicit measure/ DAX expression

• Two explicit measures/ data type

• Three explicit measures/ data category

• Two explicit measures/ DAX expression

You have a Power BI data model that contains a table named Employees. The table has the following columns:

• Employee Name

• Email Address

• Start Date

• Job Title

You are implementing dynamic row-level security (RLS).

You need to create a table filter to meet the following requirements:

• Users must see only their own employee data.

• The DAX expression must work in both Power BI Desktop and the Power BI service. Which expression should you use?

• [Email Address] - USERNAME()

• [Employee Name] - USERPRINCIPALNAME()

• [Employee Name] = USERNAME()

• [Email Address] = USERPRINCIPALNAME()

You have the Power BI data model shown in the following exhibit. The Country table contains the following data.

You create two row-level security (RLS) roles named Manager and CFO. You plan to publish the dataset to the Power BI service.

You need to create DAX expressions for the RLS filters. The solution must meet the following requirements:

• Each manager must see only the data in the Sales and Human Resources tables for their own country.

• The CFO must be prevented from seeing the data in the Human Resources table.

• The CFO must see the sales data of all countries.

How should you complete the DAX expressions to meet the requirements? To answer, drag the appropriate expressions to the correct targets. Each expression may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

• [Manager]="CFO"/[Email]= userprincipalname()

• False()/True()

• [Country]= "USA"/[Manager]="CFO"

• [Manager]="CFO"/False()

You have a Power BI data model that imports data from a Microsoft Excel spreadsheet. You use Power Query to load a query that contains both renamed and custom columns. Later, you attempt to reload the query and receive the following error message.

Expression.Error: The column 'Category' of the table wasn't found.

What are two possible causes of the error? Each correct answer presents a complete solution.

• The column was removed from the source file

• The column was renamed in the source file.

  
  

• The file is no longer in the specified location.

• The data type of the column was changed.

You have a Power BI model that contains a table named Sales. The Sales table contains the following columns:

• Order Line ID

• Product ID

• Unit Price

• Order ID

• Quantity

Orders are uniquely identified by using the order ID and can have multiple order lines. Each order line within an order contains a different product ID.

You need to write a DAX measure that counts the number of orders. Which formula should you use?

• Count('Sales'[Order ID])

• CountA('Sales' [Order ID])

• CountRows('Sales')

• DistinctCount('Sales' [Order ID])

You are creating a Power BI model in Power BI Desktop.

You need to create a calculated table named Numbers that will contain all the integers from -100 to 100.

How should you complete the DAX calculation? To answer, select the appropriate options in the answer area.

• GENERATE/(-100,100,1)

• GENERATESALL/(100,1,200)

• GENERATESERIES/(-100,100,1)

• GENERATE/(-1,-100,100)

In Power Query Editor, you have a query named Sales Data that contains the following columns.

You need to create two queries named Product Dimension and Sales Fact based on the Sales Data query. The solution must minimize maintenance effort and the size of the dataset.

Which two actions should you perform? Each correct answer presents part of the solution.

• Reference the Sales Data query to create the new queries.

• Disable the load for the Sales Fact query.

• Duplicate the Sales Data query to create the new queries.

• Clear Include in report refresh for the Sales Data query.

• Disable the load for the Sales Data query.

You have a Power BI model that contains a table named Date. The Date table contains the following columns:

• Date

• Fiscal Year

• Fiscal Quarter

• Month Name
  

• Calendar Year

• Week Number

• Month Number

• Calendar Quarter

You need to create a calculated table based on the Date table. The calculated table must contain only unique combinations of values for Calendar Year, Calendar Quarter, and Calendar Month.

Which DAX function should you include in the table definition?

• ADDCOLUMNS

• CALCULATE

• SUMMARIZE

• DATATABLE

You have a Power BI model that contains the following data.

The Date table relates to the Sales table by using the Date columns. You need to create a calculated table that will contain the following:

• A row for each year

• A column that contains the total sales per year

How should you complete the DAX calculation? To answer, select the appropriate options in the answer area.

• SUMMARIZE/Date[Year]

• ROLLUP/Sales[Date]

• SELECTCOLUMNS/Date[Date]

• ROLLUP/Date[Year]

You use Power Query Editor to import and preview sales data from the years 2020 and 2021 in a Microsoft Excel file as shown in the following exhibit.

You need to shape the query to display the following three columns:

• Month

• Sales

• Year

What should you select in Power Query Editor?

• Merge columns

  
  

• Transpose

•  Unpivot columns

•  Pivot column