Handling Missing Values in PostgreSQL

Context

Missing data is common in analytical datasets and can change counts, averages, and downstream model features if handled carelessly. In PostgreSQL, you need to understand both how NULL behaves and how to treat placeholder values such as empty strings.

Question

Explain how you would handle missing data in a dataset using SQL. Your answer should cover how you detect missing values, when you would filter them out versus replace them, and how you would preserve transparency by flagging imputed values. You should also explain the difference between real NULL values and other forms of missingness such as empty strings or sentinel values.

Scope guidance

Keep the discussion practical and PostgreSQL-focused. The interviewer is looking for clear reasoning, correct NULL handling, and a few simple SQL examples using functions such as COALESCE and CASE WHEN.