You are asked to explain how you make sure a SQL analysis is accurate and reliable before sharing it. In practice, this means validating the underlying data, checking for edge cases, and confirming that the result is internally consistent.
Describe how you would use SQL to verify the correctness of an analysis. Cover how you would check for missing values, duplicate records, unexpected joins, and aggregation mismatches. Include how you would compare totals across steps and use targeted queries to isolate anomalies.
Keep your answer focused on practical SQL validation techniques rather than general process advice. The interviewer expects you to show how you would detect data quality issues directly in PostgreSQL using queries, filters, grouping, and reconciliation logic.
You are asked to explain how you make sure a SQL analysis is accurate and reliable before sharing it. In practice, this means validating the underlying data, checking for edge cases, and confirming that the result is internally consistent.
Describe how you would use SQL to verify the correctness of an analysis. Cover how you would check for missing values, duplicate records, unexpected joins, and aggregation mismatches. Include how you would compare totals across steps and use targeted queries to isolate anomalies.
Keep your answer focused on practical SQL validation techniques rather than general process advice. The interviewer expects you to show how you would detect data quality issues directly in PostgreSQL using queries, filters, grouping, and reconciliation logic.
