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Answer: Create a view on the marketing table selecting only those fields approved for the sales team; alias the names of any fields that should be standardized to the sales naming conventions.
Option A is the simplest solution because creating a view allows the sales team to access only approved fields with aliased names without duplicating data. Views automatically reflect changes in the underlying table, avoiding the need for complex sync mechanisms (B, C) or pipeline modifications (D). B (DEEP CLONE) and C (CTAS + job) introduce data redundancy and maintenance overhead. D requires altering the production pipeline, increasing complexity.
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The marketing team needs to share aggregated data with the sales organization, but the field names differ between teams and some marketing-specific fields are not approved for sales.
Which solution best resolves this scenario while prioritizing simplicity?
A
Create a view on the marketing table selecting only those fields approved for the sales team; alias the names of any fields that should be standardized to the sales naming conventions.
B
Create a new table with the required schema and use Delta Lake's DEEP CLONE functionality to sync up changes committed to one table to the corresponding table.
C
Use a CTAS statement to create a derivative table from the marketing table; configure a production job to propagate changes.
D
Add a parallel table write to the current production pipeline, updating a new sales table that varies as required from the marketing table.
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