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Databricks Certified Data Engineer Professional · Databricks
Select one answer.
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I agree with Option B. This is the correct approach using views as an abstraction layer. Why Option B is Correct The Strategy Create new table with the updated schema (renamed fields + new fields) → Powers customer-facing app Create a view with the original schema/field names → Maintains backward compatibility for all other teams Zero disruption to BI dashboards, ML models, and ad hoc queries Single source of truth (only one physical table)
Doesn't Increase Table Count: vs Option B Removes 1 table (current aggregate table becomes a view) Adds 1 table (new table for customer-facing app) Net change: 0 tables ✅ Minimally Interrupts Other Teams: Original table name preserved as a view Existing queries continue working against the view No schema changes for existing consumers Other teams see no difference in their workflows ✅ Supports New Requirements: New table has the required field names and additional fields Customer-facing application gets exactly what it needs Optimized for the specific use case ✅
D replicates the business logic — we don't need that. It's enough to just create a view on top of the new table as mentioned in B.