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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: Transform the first row to be used as headers. 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?
Correct Answer: B
* This solution also includes transforming headers and defining column types, along with creating merged columns. However, it still does not remove rows with a high proportion of nulls. Addressing null values is important for data quality and ensuring accurate unification. * Without removing rows with many nulls, the data may still have integrity issues that could impact the unification process. As a result, this solution does not completely meet the goal.
