The implementation of fuzzy matching or partial matching should be considered a critical development priority. This feature would significantly improve both time management and data cleanliness by streamlining the identification of similar or related records, even with minor discrepancies. This would reduce the need for manual review and correction, leading to more efficient processes and higher quality data. Additionally, for Australian customers, the ability to process AUS/NZ address formats is essential to ensure accurate and reliable data handling.

We must rely on an additional tool to flag and merge duplicate records with fuzzy matching addresses because the system sees "123 Sesame Street", "123 Sesame St", and "123 Sesame St." as 3 distinct addresses; we would be doing manual override/matches all and every day otherwise. It would be helpful if the system could parse out the building number and street name and ability to add (or just baked in) fuzzy/replacement values for the street names so Dr = Drive = Dr.; St = Street = St.; PO Box = P.O. Box = POB, etc.

Fuzzy matching or partial matching is integral for both time management and data cleanliness.

Fuzzy address is critical to helping us match duplicate records

Fuzzy matching for addresses is crucial in maintaining data hygiene. Not having fuzzy matching creates a high opportunity for duplicate records to be created (since the same address being formatted differently isn't being recognized as the same). It also creates a manually intensive process for us to correct poor formatting, where this could be done automatically.