Which approach detects potential duplicates when inserting a new address record?

Which approach detects potential duplicates when inserting a new address record?

• A. Only check duplicates for users with admin role
• B. Schedule a daily batch job to compare new records with old ones
• C. Create a background check that computes a canonical form and compares against existing active addresses; flag potential duplicates for review or auto-merge when confident
• D. Ignore potential duplicates on insert

Answer: (C)

Detecting duplicates at the moment of insertion by normalizing the address and comparing it to existing records is the most effective approach. By computing a canonical form for the new address and for current addresses, the system can identify close matches despite minor variations (for example, abbreviations, punctuation, casing, or spacing). When a potential duplicate is found, it can either flag it for human review or automatically merge when the match is confident enough. This provides immediate data integrity and consistency across the database, and it works for any user, not just admins. This method is preferable to waiting for a daily batch, which delays detection and leaves a window where duplicates may slip in or diverge in quality. It’s also better than ignoring duplicates entirely, which leads to conflicting records and downstream issues.

Detecting duplicates at the moment of insertion by normalizing the address and comparing it to existing records is the most effective approach. By computing a canonical form for the new address and for current addresses, the system can identify close matches despite minor variations (for example, abbreviations, punctuation, casing, or spacing). When a potential duplicate is found, it can either flag it for human review or automatically merge when the match is confident enough. This provides immediate data integrity and consistency across the database, and it works for any user, not just admins.

This method is preferable to waiting for a daily batch, which delays detection and leaves a window where duplicates may slip in or diverge in quality. It’s also better than ignoring duplicates entirely, which leads to conflicting records and downstream issues.