SQL Validation and Profiling Techniques

Context

Data analysts regularly need to sanity-check source data before building reporting in Raymond James systems. Interviewers ask this to see whether you can quickly assess completeness, consistency, and suspicious values using straightforward SQL.

Question

Explain which PostgreSQL functions and SQL techniques you rely on most often for data validation and profiling. Your answer should cover how you check for missing values, duplicates, invalid ranges, unexpected categories, and basic distribution issues. You should also describe how GROUP BY, aggregate functions, CASE WHEN, and COALESCE help you inspect data quality in practice.

Scope guidance

Keep the answer practical and analyst-focused. You do not need to discuss advanced data quality frameworks or pipeline orchestration. Focus on the SQL patterns you would actually use first when profiling a new table or validating a feed used in Raymond James reporting.