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 questionpresents 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?
A. 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].
B. 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].
C. 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].
D. 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].
