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.
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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?

• A. Yes
• B. No

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.
You are a Customer Data Platform Specialist. Your company's information technology department (IT) has a CSV file stored on one of their Shared Documents folder within their SharePoint sites which they have ingested into audience insights. The file contains a row header with some special characters, columns of different types (quantities, prices, etc.), and some rows with a high proportion of nulls and missing primary keys. You have been asked to clean and transform the data in audience insights to be ready for unification.
What should you do?
Solution: Clean the data by transforming the first row to be used as headers and remove any special characters in header, defining column types to be appropriate field types, remove any rows with missing primary key, and name the query. Create a full name and full address columns by merging the appropriate columns if they exist.
Click "Next" and your data is now ready for unification.
Does this meet the goal?

• A. Yes
• B. No

You need to populate a marketing list in Dynamics 365 Sales with all the members of a segment in Microsoft Dynamics 365 Customer Insights. Which two conditions must be met? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

• A. The segment in Dynamics 365 Customer Insights cannot contain more than 100,000 members.
• B. The email addresses of contacts in Dynamics 365 Sales must match the corresponding unified customer profile email address field in Dynamics 365 Customer Insights.
• C. Sales team members must be assigned a role in Dynamics 365 Customer Insights to access the marketing list that is created in Dynamics 365
• D. Dynamics 365 Sales Contacts must be ingested into Dynamics 365 Customer Insights as a data source and included in the unified customer profile.

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.
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?

• A. Yes
• B. No