Explain how you handle NULL values in SQL-backed visualizations without changing the meaning of the data. Focus on when to preserve missing values, when to replace them, and how aggregate functions behave in PostgreSQL.
Understanding of `NULL` semanticsSafe use of `COALESCE`Behavior of `COUNT(*)`, `COUNT(column)`, `AVG()`, and `SUM()`Using `CASE WHEN` to expose missingness in dashboard outputsIn a Synechron visualization workflow, the interviewer is looking for practical SQL judgment: can you make a chart readable without converting missing data into false business signals?