Welcome to your interview.
The question is on your right: Ensuring SQL Data Accuracy. Take a moment with it first.
Talk your thinking through with me if you like - when you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes). Discussion and graded submissions share your five interviewer interactions, so spend them well.
Data accuracy is a core expectation in analytics and data engineering work. Interviewers ask this to understand whether you can produce trustworthy results, not just write queries that run.
Explain how you ensure data accuracy in your SQL workflow. Your answer should cover how you validate source data, check query logic, handle duplicates and nulls, verify aggregations, and confirm that final outputs match business expectations.
Keep the discussion practical. Focus on the steps you would take while writing and reviewing SQL: profiling raw data, applying filters carefully, validating joins, reconciling row counts and totals, and using simple checks to catch mistakes before sharing results. You can mention examples such as comparing pre- and post-transformation counts, checking for unexpected nulls, or validating totals against a trusted source.