Explain how you would handle missing or NULL values in a PostgreSQL dataset before starting analysis. Focus on a practical workflow: identify missingness, decide whether to keep, filter, or replace NULLs, and explain how simple SQL tools support those choices.
Data profiling with basic aggregationsUsing `COALESCE` and `CASE WHEN` appropriatelyUnderstanding how NULLs affect counts and averagesMaking business-aware cleaning decisionsKeep the answer at an analyst level. You do not need advanced statistical imputation. A strong answer is structured, SQL-aware, and clear about tradeoffs.