Handling Missing Data in PostgreSQL

Context

Missing data is common in reporting and analysis, especially when working with operational exports, OpenText analytics datasets, or partially completed records. If you handle it poorly, your counts, averages, and downstream conclusions can be misleading.

Core question

Explain how you would handle missing data in a dataset using PostgreSQL. Your answer should cover how you would detect missing values, decide whether to filter, replace, or preserve them, and how functions such as COALESCE, CASE WHEN, and aggregate functions behave with NULL values.

Scope guidance

Keep your answer practical and analyst-focused. The interviewer is looking for a clear explanation of trade-offs, common SQL techniques, and how you would avoid introducing incorrect assumptions while preparing data for analysis or reporting.