How to perform fuzzy matching in SQL

Ever struggled with matching names like 'John Smith' and 'Jon Smyth' in your database? 🤔 Fuzzy matching is your secret weapon!

This carousel breaks down three popular techniques to perform fuzzy matching in SQL:

1️⃣ SOUNDEX(): Perfect for matching names that sound similar. It's a built-in function that's easy to use but works best for English phonetics.

2️⃣ Levenshtein Distance: The go-to for catching typos! It calculates the number of edits needed to change one string into another. A lower score means a closer match.

3️⃣ Trigrams (N-grams): A powerful method that splits strings into smaller chunks and compares them. It's incredibly fast, especially with an index, and great for finding partial matches.

Which one should you use? It depends on your data and the types of errors you're trying to catch. Swipe through to see them in action!

Which method do you prefer, or do you use another technique? Drop your thoughts in the comments below! 👇

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