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You are configuring a new Dynamics 365 Customer Insights - Data environment that is focused on business accounts. You have completed business account unification, and you are now setting up contact unification.

You need to configure a relationship between a contact table and an account table.

Which two values do you need to specify on the Relationships page? Each correct answer presents part of the solution.

MOTE: Each correct selection is worth one point.

Your company uses both Dynamics 36$ Customer Insights - Data and Dynamics 365 Sates. To enhance the customer information within Dynamics 365. the administrators added the Customer Insights - Data timeline as a Customer Card Add-in control on the contact form.

You need to update the company's Dynamics 365 user guide and explain how users can use the timeline.

Which actions can users perform from the Customer Insights - Data timeline on a Dynamics 365 form?

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 Dynamics 365 Customer Insights - Data.

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 Customer Insights - Data to be ready for unification.

Solution: Transform the first row to be used as headers, remove rows that contain null values, and name the query. Select Next and your data is now ready for unification.

Does this meet the goal?

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 Dynamics 365 Customer Insights - Data.

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 Customer Insights - Data to be ready for unification.

Solution: Remove any rows where the primary key is missing, delete any leading or trailing zeros on the primary key, and name the query. Select Next and your data is now ready for unification.

Does This meet the goal?

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 Dynamics 365 Customer Insights - Data.

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 Customer Insights - Data to be ready for unification.

Solution: Define column types to be appropriate field types, and name the query. Create a full name and full address columns by merging the appropriate columns if they exist. Select Next and your data is now ready for unification.

Does This meet the goal?