PL-300 Exam Dumps - Microsoft Power BI Data Analyst

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Question # 17

You need to design the data model to meet the report requirements.

What should you do in Power BI Desktop?

From Power Query, use a DAX expression to add columns to the Orders table to calculate the calendar quarter of the OrderDate column, the calendar month of the OrderDate column, the calendar quarter of the ShippedDate column, and the calendar month of the ShippedDate column.

From Power Query, add columns to the Orders table to calculate the calendar quarter and the calendar month of the OrderDate column.

From Power Bl Desktop, use the Auto date/time option when creating the reports.

From Power Query, add a date table. Create an active relationship to the OrderDate column in the Orders table and an inactive relationship to the ShippedDate column in the Orders table.

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Question # 18

You need to configure access for the sales department users. The solution must me meet the security requirements. What should you do?

Add the sales department as a member of the reports workspace

Add the Azure Active Directory group of the sales department as an Admin of the reports workspace.

Distribute an app to the users in the Azure Active Directory group of the sales department.

Share each report to the Azure Active Directory group of the sales department.

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Question # 19

You need to create the dataset. Which dataset mode should you use?

DirectQuery

Import

Live connection

Composite

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Question # 20

You need to minimize the size of the semantic model. The solution must meet the report requirements.

What should you do?

Filter out discontinued products while importing the Products table.

Group the Categories table by the CategorylD column.

Change the OrderlD column in the Orders table to the Text data type.

Remove the QuantityPerUnit column from the Products table.

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Question # 21

You need to create a measure that will return the percentage of late orders.

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

NOTE: Each correct selection is worth one point.

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Answer:

Explanation:

Box 1: CALCULATE

CALCULATE evaluates an expression in a modified filter context.

Syntax: CALCULATE([, [, [, â€¦]]])

Expression - The expression to be evaluated.

filter1, filter2,â€¦ (Optional) Boolean expressions or table expressions that defines filters, or filter modifier functions.

Box 2: FILTER

FILTER returns a table that represents a subset of another table or expression.

Syntax: FILTER(

Table- The table to be filtered. The table can also be an expression that results in a table.

Filter - A Boolean expression that is to be evaluated for each row of the table. For example, [Amount] > 0 or [Region] = "France"

Box 3: Orders[ShippedDate]> Orders[RequiredDate]

Northwind Traders defines late orders as those shipped after the required shipping date.

[Reference:, https://docs.microsoft.com/en-us/dax/calculate-function-dax, , https://docs.microsoft.com/en-us/dax/filter-function-dax, , ]

Question # 22

You need to minimize me size of the dataset. The solution must meet the report requirements What should you do?

Change lite OrderlD column in the Orders table to the text data type.

Filter out discontinued products while importing the Product table.

Remove the QuantityPerUnit column from the Products table

Group the Categories table by the CategorylD column.

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Question # 23

You need to create relationships to meet the reporting requirements of the customer service department.

What should you create?

an additional date table named ShipDate, a one-to-many relationship from

Sales[sales_date_id] to Date[date_id], and a one-to-many relationship from

Sales[sales_ship_date_id] to ShipDate[date_id]

an additional date table named ShipDate, a many-to-many relationship from

Sales[sales_date_id] to Date[date_id], and a many-to-many relationship from

Sales[sales_ship_date_id] to ShipDate[date_id]

a one-to-many relationship from Date[date_id] to Sales[sales_date_id] and another one-to-many relationship from Date[date_id] to Weekly_Returns[week_id]

a one-to-many relationship from Sales[sales_date_id] to Date[date_id] and a one-to-many

relationship from Sales[sales_ship_date_id] to Date[date_id]

a one-to-many relationship from Date[date_id] to Sales[sales_date_id] and another one-to-many relationship from Date[date_id] to Sales[sales_ship_date_id]

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