Microsoft
70-778 · Question #148
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…
The correct answer is B. In the Monthly_returns table, create a new calculated column named Date_ID that uses the. https://docs.microsoft.com/en-us/power-bi/desktop-create-and-manage-relationships
Model and Visualize Data by Using Power BI Desktop
Question
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 relationship between the Monthly_returns table and Date[Date_ID]. What should you do before you create the relationship?
Exhibit
Options
- AIn the Date table, create a new calculated column named Month_ID that uses the yyyydd format.
- BIn the Monthly_returns table, create a new calculated column named Date_ID that uses the
- CTo the Order table, add a calculated column that uses the RELATED(Monthly_returns[Month_ID])
- DTo the Date table, add a calculated column that uses the RELATED(Monthly_returns[Month_ID])
How the community answered
(25 responses)- A8% (2)
- B72% (18)
- C16% (4)
- D4% (1)
Explanation
https://docs.microsoft.com/en-us/power-bi/desktop-create-and-manage-relationships
Topics
#calculated columns#date relationships#data model#table joins
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