Q1
Walk me through how you would optimize a SQL query that joins five tables and is currently taking 45 seconds to execute on a dataset with 100 million rows. What tools would you use to diagnose the problem?
Why they ask this:* They want to assess your practical SQL optimization skills, understanding of query execution plans, indexing strategies, and ability to diagnose performance bottlenecks—critical for handling large datasets efficiently.
Q2
Describe a time you built a dashboard in Tableau or Power BI. How did you decide which visualizations to use, and how did you ensure the data was accurate before publishing it to stakeholders?
Why they ask this:* They're evaluating your hands-on experience with BI tools, your ability to translate business requirements into effective visualizations, and your quality assurance processes.
Q3
Explain the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN with a real-world data scenario where you would use each one. Why is choosing the correct join type critical?
Why they ask this:* This tests fundamental SQL knowledge and your ability to think about data relationships logically—essential for accurate analysis and preventing silent data errors.
Q4
You discover that a dataset has missing values in 30% of a critical column. How would you approach this problem: would you exclude those rows, impute the data, or use another method? What factors would influence your decision?