How should you model physical versus mailing addresses in data?

How should you model physical versus mailing addresses in data?

• A. Use a single flag to indicate physical vs mailing
• B. Use separate fields only
• C. Support both with a flag or separate fields and allow duplication if needed
• D. Treat them as the same address

Answer: (C)

Think about addresses as two distinct but related roles: where someone actually lives (physical) and where mail should be sent (mailing). A robust model captures both by storing address components in structured fields (street, city, state, postal code, country) and tagging each address with its purpose. The best approach lets you have multiple address records for one person, each with its own type indicator (physical, mailing, or both), and it allows duplicating address data when needed. This provides the flexibility to handle cases where the physical and mailing addresses differ, where they’re the same, and where a person might have more than one of either type, which is common in real-world data.

Using a single flag alone forces one address to cover both roles and makes it hard to manage cases where two distinct addresses exist. Relying on separate fields only can be inflexible and unwieldy as you scale to multiple addresses. Treating physical and mailing addresses as the same ignores practical differences and can lead to incorrect mailings or shipments.