MB-260

Question 26

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. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are a Customer Data Platform Specialist. Your company's information technology department already ingested a CSV file with column names in the first row into audience insights. You are asked to clean and transform the data to get it ready for unification. What can you do to satisfy the requirements? Solution: Clean the data by changing columns with numbers to integer number format, which includes fields such as price, number of purchases, and postal code. You should convert primary key to integer number field if it contains only numbers. Click `Next` and your data is now ready for unification. Does this meet the goal?

1. Yes
2. No

Question 27

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. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are a Customer Data Platform Specialist. Your company's information technology department already ingested a CSV file with column names in the first row into audience insights. You are asked to clean and transform the data to get it ready for unification. What can you do to satisfy the requirements? Solution: Clean the data by removing any rows with nulls and deleting any leading zeros on the primary key. Click `Next` and your data is now ready for unification. Does this meet the goal?

1. Yes
2. No

Question 28

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. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. A company's IT department has a CSV file stored on one of their Shared Documents folders within their Microsoft SharePoint sites. The data from the CSV file is ingested into Microsoft Dynamics 365 Customer Insights. The file contains a row header and columns of different types, such as quantities and prices. The file also contains some rows with a high proportion of nulls. You need to clean and transform the data in Dynamics 365 Customer Insights to be ready for unification. Solution: Transform the first row to be used as headers, define column types to be the appropriate field types and name the query. Select Next and your data is now ready for unification. Does this meet the goal?

1. Yes
2. No

Question 29

An organization uses Microsoft Power Query when connecting to data sources in Microsoft Dynamics 365 Customer Insights. You add an eCommerce Contacts data source to Dynamics 365 Customer Insights. The table contains the Contact's date of birth (DOB). You need to add an Age column, so that it is available in Dynamics 365 Customer Insights. Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Question 30

You are working on implementing data refreshes in Microsoft Dynamics 365 Customer Insights. You need to make sure the Dynamics 365 Customer Insights processes run regularly through either manual on-demand refreshes or scheduled refreshes. Which two statement apply to refreshing data in Dynamics 365 Customer Insights? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

1. If the data refreshes fail when running a scheduled refresh, all downstream processes stop with Failed or Skipped status.
2. It is possible to manually run on-demand data refreshes for one or more data sources even when a schedule is set.
3. When running on demand refresh, match and merge are automatically queued after the data source refresh completes.
4. Once data refreshes are in-progress, users can simultaneously run match and merge processes.