Sep 27

Top 40 SQL Data Analyst Interview Questions with answers 2024

Introduction

In Data Analyst interviews, SQL questions assess your proficiency in handling data extraction, transformation, and analysis. The aim is to evaluate your problem-solving skills and query optimization. These questions vary in difficulty from basic queries to complex case studies and are intended to test your ability to write clean, efficient, and accurate SQL code.

In this blog, we'll explore the top 40 SQL Data Analyst interview questions, categorized into easy, intermediate, and hard levels, to help you prepare thoroughly for your upcoming interview.

1. Overview of SQL Questions

2. How SQL Is Tested in Data Analyst Interviews

#1 Whiteboard Tests

Candidates write SQL queries on a whiteboard to demonstrate their thought process and syntax understanding.

#2 Live Coding Tests

Candidates are asked to run queries live in a coding environment, providing an opportunity to debug and improve code in real-time.

#3 SQL Case Studies

Candidates solve real-world problems using SQL, which assesses both technical ability and creative problem-solving skills.

3. Easy SQL Questions for Data Analysts

1. What is the purpose of the GROUP BY clause?

GROUP BY allows you to aggregate data based on one or more columns. It is commonly used with aggregate functions like COUNT, SUM, AVG, MAX, and MIN.

Example:

2. Define and explain the most common aggregate functions in SQL.

  • COUNT: Returns the number of items in a group.
  • SUM: Calculates the sum of a set of values.
  • AVG: Finds the average of a group of values.

Example:

3. What is a unique key?

A unique key is a column or a set of columns in a table that uniquely identifies each row. It allows one NULL value and prevents duplicate entries.

4. What is the difference between UNION and UNION ALL?

  • UNION: Combines results from two queries and removes duplicates.
  • UNION ALL: Combines results and retains duplicates.

Example:

5. How does a LEFT JOIN differ from a RIGHT JOIN?

  • LEFT JOIN: Returns all rows from the left table and matched rows from the right.
  • RIGHT JOIN: Returns all rows from the right table and matched rows from the left.

6. What is the difference between a table and a view?

  • Table: A collection of data stored physically in a database.
  • View: A virtual table based on the result set of an SQL query.

7. What is the LIKE operator used for?

The LIKE operator is used for pattern matching in a WHERE clause.

Example:

8. How do you update data in a table?

Use the UPDATE statement with SET to modify records.

9. What does the BETWEEN operator do?

The BETWEEN operator selects values within a specified range, inclusive of start and end values.

10. Write a query to select a random row from a table.

Example:

4. Intermediate SQL Questions for Data Analysts

11. Find the 3 lowest-paid employees who have completed at least 2 projects.

Use joins and aggregation to filter by project completion and order by salary.

12. How to calculate the total distance traveled by each user and order by the highest?

Group by user_id and sum the distance traveled.

Example:

13. Write a query to find users who are currently "Excited" but have never been "Bored".

Use conditional grouping and filtering with NOT EXISTS or LEFT JOIN to exclude users with a "Bored" status.

14. How to find the second-highest salary in a department?

Use window functions such as RANK() or DENSE_RANK().

15. Write a query to retrieve the last transaction of each day.

Partition transactions by date and order by timestamp.

16. Debug a query and find the top five projects by budget-to-employee ratio.

Group by project, calculate the budget per employee, and use ranking functions to find the top 5.

17. Derive insights from a table that tracks daily message counts on a social media platform.

Discuss metrics like total messages per day, peak message times, and average message length.

18. Create a histogram for the number of comments per user in January 2020.

Group by user_id and use the COUNT() function.

19. Find the top three largest departments ranked by employees earning over $100,000.

Calculate percentages of employees meeting the condition and order the results.

20. Find two students with the closest SAT scores.

Use self-joins to compare every pair of rows and find the minimum score difference.

5. Hard SQL Questions for Data Analysts

21. Analyze whether CTR (Clickthrough Rate) is dependent on search rating.

Group by rating levels and calculate the CTR.

22. Write a query to count customers who were upsold by purchasing additional products.

Compare transaction dates for each user to identify repeat purchases.

23. How to find the third purchase of every user?

Use window functions like ROW_NUMBER() to rank purchases by date.

24. Identify users who posted each of their job listings only once and those with multiple posts.

Group by user and job listings to count occurrences.

25. Write a query to return the top three salaries in each department.

Use RANK() or DENSE_RANK() with PARTITION BY department.

26. Find the number of unsold seats for each flight.

Join flights, planes, and flight_purchases tables to calculate unsold seats.

27. Sample every fourth row ordered by date in a transactions table.

Use ROW_NUMBER() with a modulus condition.

28. Find neighborhoods with zero users.

Use a LEFT JOIN between neighborhoods and users, filtering NULL values.

29. How would you measure the success of a new feature allowing buyer-seller audio chats?

Discuss metrics like user adoption rate, call completion rate, and transaction increase.

30. Calculate a three-day rolling average for bank deposits.

Use window functions with SUM() and ROWS BETWEEN.

31. Create a cumulative distribution for comments per user.

Rank comments by user and calculate cumulative frequency.

32. How to visualize the impact of user unsubscriptions on login rates over time?

Calculate the number of unsubscribes and plot them against login frequency.

33. Evaluate if data scientists who switch jobs frequently become managers faster.

Segment data by job switches and analyze promotion timelines.

34. Calculate the distribution of total push notifications before user conversion.

Analyze user activity data before a purchase to find patterns in notification interactions.

35. Find top paired products often purchased together.

Join transactions on different product IDs and calculate the frequency of pairs.

36. Write a query to identify "silent" users who haven't engaged in the past month.

Check for users without any recent activity.

37. How to find duplicate rows in a table?

Use GROUP BY on all columns and apply COUNT() > 1.

38. Write a query to display users with the maximum login sessions per day.

Group logins by user and date, then find the maximum count.

39. Calculate the percentage of revenue generated by each product category.

Join products with sales, group by category, and calculate the percentage.

40. Write a query to identify products with no sales in the last year.

Perform a LEFT JOIN between products and sales, filtering by the date condition.

Conclusion

These top 40 SQL Data Analyst interview questions provide a comprehensive foundation for understanding different SQL concepts, techniques, and problem-solving approaches. By practicing these questions, you'll gain confidence in answering SQL queries efficiently and effectively during interviews.

For more practice, quizzes, and in-depth explanations, check out FreshersUtopia's SQL interview prep courses and resources.
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