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Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You have a Power BI model that contains two tables named Sales and Date. Sales contains four columns named TotalCost, DueDate, ShipDate, and OrderDate. Date contains one column named Date.

The tables have the following relationships:
• Sales[DueDate] and Date[Date]
• Sales[ShipDate] and Date[Date]
• Sales[OrderDate] and Date[Date]

The active relationship is on Sales[DueDate].

You need to create measures to count the number of orders by [ShipDate] and the orders by [OrderDate]. You must meet the goal without duplicating data or loading additional data.

Solution: You create a calculated table. You create a measure that uses the new table. Does this meet the goal?

  1. Yes
  2. No

Answer(s): B



You have a Power BI Desktop project that uses DirectQuery to access an on-premises Microsoft SQL Server database.

From Power BI Desktop, you can query the database.
When you publish the Power BI Desktop project to the Power BI service, the visualizations cannot display the data.

What should you do to resolve the issue?

  1. Locate the published dataset for the project in the Power BI service and configure the data source credentials.
  2. Install the on-premises data gateway (personal mode) and republish the project.
  3. Install the on-premises data gateway and configure a data source.
  4. Configure a Microsoft Azure ExpressRoute connection between the on-premises network and the Power BI service.

Answer(s): C


Reference:

https://docs.microsoft.com/en-us/power-bi/service-gateway-sql-tutorial



Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is the same in each question in this series.

You have a Microsoft SQL Server database that contains the following tables.


The following columns contain date information:

• Date[Month] in the mmyyyy format
• Date[Date_ID] in the ddmmyyyy format
• Date[Date_name] in the mm/dd/yyyy format
• Monthly_returns[Month_ID] in the mmyyyy format

The Order table contains more than one million rows.

The Store table has a relationship to the Monthly_returns table on the Store_ID column. This is the only relationship between the tables.

You plan to use Power BI Desktop to create an analytics solution for the data.
You need to create a chart that displays a sum of Order[Order_amount] by month for the Order_ship_date column and the Order_date column.

How should you model the data?

  1. Create a one-to-many relationship from Date[Date_ID] to Order[Order_date] and another relationship from Date[Date_ID] to Monthly_returns[Date_ID].
  2. Add a second Date table named Ship_date to the model. Create a many-to-many relationship from Date [Date_ID] to Order[Order_date] and many-to-many relationship from Ship_date[Date_ID] to Order [Order_ship_date].
  3. Add a second Date table named Ship_date to the model. Create a one-to-many relationship from Date [Date_ID] to Order[Order_date] and a one-to-many relationship from Ship_Date[Date_ID] to Order [Order_ship_date].
  4. Create a one-to-many relationship from Date[Date_ID] to Order[Order_date] and another relationship from Date[Date_ID] to Order[Order_ship_date].

Answer(s): C



Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is the same in each question in this series.

You have a Microsoft SQL Server database that contains the following tables.


The following columns contain date information:

• Date[Month] in the mmyyyy format
• Date[Date_ID] in the ddmmyyyy format
• Date[Date_name] in the mm/dd/yyyy format
• Monthly_returns[Month_ID] in the mmyyyy format

The Order table contains more than one million rows.
The Store table has a relationship to the Monthly_returns table on the Store_ID column. This is the only relationship between the tables.

You plan to use Power BI Desktop to create an analytics solution for the data.
You are modeling the data in Power BI.
You need to import only a sample of the data from the Order table.

What are two possible ways to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  1. From Query Editor, create a custom column that uses a custom column formula.
  2. From Query Editor, add a SELECT statement that uses a WHERE clause to the source definition.
  3. In the Power BI model, create a calculated table.
  4. From Query Editor, filter the table by Order_date.
  5. From Query Editor, create a column by using Column From Examples.

Answer(s): B,D



Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is the same in each question in this series.

You have a Microsoft SQL Server database that contains the following tables.


The following columns contain date information:

• Date[Month] in the mmyyyy format
• Date[Date_ID] in the ddmmyyyy format
• Date[Date_name] in the mm/dd/yyyy format
• Monthly_returns[Month_ID] in the mmyyyy format

The Order table contains more than one million rows.
The Store table has a relationship to the Monthly_returns table on the Store_ID column. This is the only relationship between the tables.

You plan to use Power BI Desktop to create an analytics solution for the data. You are modifying the model to report on the number of orders.
You need to calculate the number of orders. What should you do?

  1. Create a calculated measure that uses the COUNTA(Order_ID) DAX formula.
  2. Create a calculated column that uses the COUNTA(Order_ID) DAX formula.
  3. Create a calculated column that uses the SUM(Order_ID) DAX formula.
  4. Create a calculated measure that uses the SUM(Order_ID) DAX formula.

Answer(s): A