Your question is Verifying Discrepant Event Log Data. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Data discrepancies in operational logs can affect reporting, customer messaging, and downstream workflows. In a system like Klaviyo, you often need to confirm whether an unexpected count or missing event reflects a real issue, a logging delay, or a join/filter mistake.
If you found a discrepancy in an event log, explain how you would verify the information using SQL. Describe how you would reconcile the log against a source-of-truth table, what aggregate checks you would run first, how you would use joins to isolate missing or duplicated records, and how you would validate whether the discrepancy is caused by timing, null keys, or transformation logic.
The interviewer is looking for a practical verification framework, not just a definition of reconciliation. You should be able to talk through the order of checks, the SQL patterns you would use, and how you would distinguish a true data issue from a query or pipeline issue.