Describe how you ensure a SQL analysis is accurate when the underlying financial data is incomplete, duplicated, delayed, or inconsistent. Focus on how you inspect data quality, validate joins, handle missing values, and avoid producing misleading metrics.
How you profile raw data before analysisHow you validate join logic and row-count changesHow you handle NULLs, duplicates, and conflicting recordsHow you communicate assumptions and reconcile final outputsIn portfolio and recovery reporting, small data issues can materially change balances, liquidation rates, or payment trends. The interviewer is looking for a methodical SQL workflow, not just a generic statement about “cleaning the data.”