Which practice helps validate that data mappings remain correct after changes in the external system?

• A. Regularly re-run mapping tests with representative data.
• B. Ignore changes and assume it's still correct.
• C. Only test mappings when asked by auditors.
• D. Rely on manual data entry instead of automated mappings.

Answer: (A)

Keeping data mappings accurate after changes in the external system relies on regularly re-running mapping tests with representative data. This approach directly validates that each mapping rule, field alignment, data type, and any transformation logic still works as intended when the external system evolves. Using representative data ensures you exercise real-world scenarios and edge cases, so issues are caught before they impact production. Automating these tests provides consistent, timely feedback whenever external changes occur, helping prevent silent data drift and potential processing errors.

Others fall short because ignoring changes lets mismatches accumulate, and testing only when auditors ask is reactive rather than proactive. Relying on manual data entry cannot verify automated mappings and is error-prone and not scalable.