Databricks Certified Data Engineer - Professional
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A data engineering team maintains aggregate tables that support BI dashboards, machine learning models, and ad hoc analytics across an organization. A customer-facing application—the only workload directly managed by the data engineering team—requires renaming several existing fields and adding new ones to a shared aggregate table.
Which solution addresses these requirements while minimizing disruption to other teams and avoiding excessive management of multiple tables?
A
Create a new physical table with the updated schema for the customer-facing application, then replace the original table identifier with a view that aliases the new table's fields to match the original schema.
B
Notify all organizational stakeholders of the mandatory schema change and provide documentation on how to refactor their legacy queries to match the updated field names.
C
Utilize Delta Lake's deep clone functionality to create a synchronized copy of the table, applying the schema changes only to the cloned version while keeping the original intact.
D
Replace the current table with a logical view to preserve existing query logic for other teams, while creating an entirely separate, independent physical table to serve the customer-facing application.