Fuzzy matching used to join tables
"Fuzzy matching used to join tables" is one of the reliability checks Auditabi runs on a Power BI semantic model. n query(ies) join with fuzzy matching. It is a medium-severity finding: the model still works, but results are wrong in some filter contexts, slow, or fragile under change. Join on a real key; keep fuzzy matching for a one-off cleanup, never for a scheduled refresh.
What is detected
n query(ies) join with fuzzy matching. The result depends on a similarity threshold: rows match today and stop matching when a label changes slightly, with no error raised.
Why it matters
Wrong in some filter contexts, slow, or fragile under change. Fix in the next iteration.
How to fix it
Join on a real key; keep fuzzy matching for a one-off cleanup, never for a scheduled refresh.
Does your model fail this check?
Free static audit with the exact objects, no account, nothing stored.