Context

Teams often build weekly performance reports from operational tables that contain nulls, blank strings, duplicate rows, and inconsistent status values. A good analyst or data engineer should be able to explain how they would make the report reliable before calculating metrics.

Question

How would you handle missing or messy data when preparing a weekly performance report in SQL? In your answer, explain:

1. How you would identify common data quality issues
2. How you would standardize or clean values before aggregation
3. How you would treat nulls, blanks, duplicates, and invalid numeric values
4. How you would make sure weekly metrics remain consistent and interpretable

Scope Guidance

The interviewer is looking for a practical SQL-focused explanation, not just general data cleaning advice. Discuss the logic you would apply in PostgreSQL, the trade-offs of imputing versus excluding records, and how your choices affect weekly aggregates such as counts, sums, and averages.