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NEW QUESTION 52
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 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?

A. NoB. Yes

Answer: B

Explanation:
Reference:
https://docs.microsoft.com/en-us/dynamics365/customer-insights/audience-insights/connect-power-query

 

NEW QUESTION 53
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. NoB. Yes

Answer: A

Explanation:
Reference:
https://docs.microsoft.com/en-us/dynamics365/customer-insights/audience-insights/connect-power-query

 

NEW QUESTION 54
You are a Customer Data Platform Specialist. Your company's information technology team wants to use the out-of-the-box customer lifetime value (CLV) machine learning (ML) capabilities that come with audience insights, but the team has some concerns about the suitability of their dat
a. You need to confirm if their research about data requirements is correct.
Which two statements are correct about the data characteristic requirements for configuring the CLV ML model? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. There should be preferably two to three years of transactional data to predict CLV for one year.B. There should be at least 100.000 unique customers to perform the CLV model.C. There should be at least two to three transactions per customer ID. preferably across multiple dates.D. The CLV model will not run if there is any missing data in the fields.

Answer: A,C

Explanation:
Reference:
https://docs.microsoft.com/en-us/dynamics365/customer-insights/audience-insights/predict-customer-lifetime-value

 

NEW QUESTION 55
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