Your question is Handling Missing Data in SQL. 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).
Missing data shows up constantly in product analysis, especially in event logs and profile fields on surfaces like Quora feed impressions, answers, and signup flows. Interviewers want to see that you can distinguish between truly missing values, valid zeroes, and rows that should be excluded.
Explain how you handle missing data in a SQL-based analysis. You should describe how you identify missing values, decide whether to filter, impute, or label them, and how functions like COALESCE, CASE WHEN, and aggregate functions affect the result. You should also explain how your approach changes depending on whether the missing field is a metric, dimension, or date.
Keep your answer practical rather than theoretical. The interviewer expects you to discuss common SQL patterns, trade-offs, and how missing data can bias product metrics if handled incorrectly.