Fuzzy Matching

Fuzzy matching is used in data cleaning to catch records that would be missed because of small spelling differences, missing characters, or formatting inconsistencies. It is especially important for free-text fields such as names, addresses, company titles, and product descriptions. Techniques such as Levenshtein distance, token similarity, and phonetic matching may be used in this process. However, similarity does not always mean identity, so fuzzy matching should always be supported with business rules and contextual knowledge.