Microsoft MB-260 Exam Practice Questions (P. 3)

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 (IT) has a CSV file stored on one of their Shared Documents folders 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 removing any rows where the primary key is missing, delete any leading or trailing zeros on the primary key, and name the query. Click
`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.
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 removing special characters and spaces from header row, defining column types to be appropriate field types, remove rows with missing primary keys, and name the query. Click `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.
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?

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 transforming the first row to be used as headers, defining column types to be appropriate field types, and naming the query. Create a full name column if it does not exist by merging the columns for the first name and last name. Click `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.
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?