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 Order table and the Store table on the Store_ID column. What should you do before you create the relationship?

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 Order table and the Store table on the Store_ID column. What should you do before you create the relationship?

Accepted Answer

C. In the Store table query, use the Table.TrasformColumnTypes function. The `Table.TransformColumnTypes` function in Power Query Editor is specifically designed to change the data type of one or more columns within a table, which is crucial for ensuring data consistency and enabling relationships like the one between the Store and Monthly_returns tables.

Answer

A. In the Order table query, use the Table.TrasformRows function. The `Table.TransformRows` function applies a transformation to each row based on row-level logic, which is not the primary or most efficient method for simply changing column data types, and is applied to the wrong table.

Answer

B. In the Store table query, use the Table.TrasformRows function. The `Table.TransformRows` function applies a transformation to each row based on row-level logic, which is not the primary or most efficient method for simply changing column data types.

Answer

D. In the Order table query, use the Table.TrasformColumnTypes function. While `Table.TransformColumnTypes` is correct for changing data types, this option applies the transformation to the `Order` table, not the `Store` table, making it incorrect if the data type issue resides within the `Store` table.

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 cho

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