Data Analyst Interview Questions with Answers: Part-2 🧠

11. What is a subquery?
A subquery is a query nested inside another SQL query (like SELECT, INSERT, UPDATE, DELETE). It returns data used by the outer query.
Example:
SELECT name FROM students WHERE marks > (SELECT AVG(marks) FROM students);

12. Explain GROUP BY and HAVING clause
• GROUP BY: Groups rows by a column's values for aggregation (SUM(), COUNT(), etc.)
• HAVING: Filters aggregated results (like WHERE for groups)
Example:
SELECT department, COUNT(*) FROM employees GROUP BY department HAVING COUNT(*) > 5;

13. What are window functions in SQL?
Window functions perform calculations across a set of rows related to the current row without collapsing rows.
Example: ROW_NUMBER(), RANK(), LEAD(), LAG()
SELECT name, department, RANK() OVER(PARTITION BY department ORDER BY salary DESC) FROM employees;

14. Difference between RANK(), DENSE_RANK(), ROW_NUMBER()
• ROW_NUMBER(): Unique rank even if values are the same
• RANK(): Skips ranks for ties
• DENSE_RANK(): No rank gaps for ties
Example: If two people tie at 2nd place:
• RANK: 1, 2, 2, 4
• DENSE_RANK: 1, 2, 2, 3
• ROW_NUMBER: 1, 2, 3, 4

15. What is a CTE in SQL?
CTE (Common Table Expression) is a temporary result set defined with WITH for better readability and reuse in a query.
Example:
WITH HighEarners AS (
SELECT name, salary FROM employees WHERE salary > 100000
)
SELECT * FROM HighEarners;

16. What is the difference between WHERE and HAVING?
• WHERE: Filters before grouping (on individual rows)
• HAVING: Filters after grouping (on aggregates)
Example:
SELECT department, COUNT(*) FROM employees
WHERE active = 1
GROUP BY department
HAVING COUNT(*) > 10;

17. Explain data types in SQL
Data types define the kind of data a column can store:
• INT, FLOAT – Numeric
• VARCHAR, TEXT – Strings
• DATE, DATETIME – Time values
• BOOLEAN – True/False values

18. How do you handle NULL values in SQL?
• Use IS NULL or IS NOT NULL
• Use functions like COALESCE() to replace NULLs
Example:
SELECT COALESCE(phone, 'Not Provided') FROM customers;

19. What are common data visualization tools?
• Power BI
• Tableau
• Google Data Studio
• Excel
• Python libraries: Matplotlib, Seaborn, Plotly

20. When would you use a bar chart vs pie chart?
• Bar chart: Compare multiple categories clearly
• Pie chart: Show proportions of a whole (best for 2–5 categories)
Bar charts are generally more accurate and readable.

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