Your question is Wrangling Messy Financial Data. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Financial datasets often contain missing values, inconsistent date formats, duplicate transactions, and invalid amounts. In analytics and reporting, poor data wrangling leads directly to incorrect revenue, expense, and cash flow numbers.
Explain how you would perform data wrangling on a messy financial dataset using SQL in PostgreSQL. Your answer should cover:
The interviewer is looking for a practical SQL-oriented explanation, not a full ETL architecture. Focus on common cleaning patterns, the order of operations, and how you would make the dataset reliable enough for financial analysis.
