Introduction

So, you've landed that coveted data analyst, data scientist, or backend engineer interview. Congratulations! Now comes the nerve-wracking part: the technical SQL interview. SQL remains a fundamental skill for many tech roles, and interviewers love to test your ability to manipulate and retrieve data efficiently.

While the range of potential SQL questions can seem vast, a core set of concepts appears time and time again. Mastering these will significantly boost your confidence and performance. This guide highlights seven critical SQL interview questions/topics you absolutely need to practice to be 90% ready for what comes your way. Plus, we'll explore how modern AI tools can be your secret weapon in preparing.

Why These SQL Concepts Matter in Interviews

Interviewers don't just want to see if you can write a basic SELECT * FROM table. They're assessing your:

• Problem-Solving Ability: Can you understand a data problem and translate it into a logical SQL solution?

• Understanding of Relational Databases: Do you grasp concepts like primary/foreign keys, joins, and data relationships?

• Efficiency: Can you write queries that are not only correct but also performant?

• Attention to Detail: SQL syntax can be unforgiving. Accuracy matters.

• Practical Application: These questions often reflect real-world scenarios analysts and engineers face daily.

By focusing on these core areas, you demonstrate a solid foundation that employers are actively seeking.

The Top 7 SQL Interview Question Categories to Master

1. How to Find Duplicates

Why it's asked: Tests your understanding of GROUP BY, HAVING, and window functions like ROW_NUMBER().

Common Scenarios: Data cleaning, identifying duplicate entries, maintaining data integrity.

Key Techniques:

• GROUP BY with HAVING COUNT(*) > 1

• Use of ROW_NUMBER() in a CTE to isolate duplicate entries

Practice Tip with AI2sql: Ask, "Show me all customers with the same email address" or "Identify duplicate orders based on order ID and customer ID."

2. How to Calculate Running Totals

Why it's asked: Demonstrates your ability to use window functions for analytical insights.

Common Scenarios: Sales growth, user acquisition over time, inventory tracking.

Key Techniques:

• SUM(...) OVER (ORDER BY ...)

• Partitioning using PARTITION BY for grouped totals

Practice Tip with AI2sql: Try, "Calculate running total of sales for each month" or "Cumulative sign-ups by date."

3. How to Join Multiple Tables

Why it's asked: Relational data is core to SQL; joins are unavoidable.

Common Scenarios: Combining user data with transactions, linking products to sales, etc.

Key Techniques:

• INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN

• Matching primary and foreign keys

Practice Tip with AI2sql: Ask, "List all customers and the products they ordered."

4. How to Filter Using Subqueries

Why it's asked: Tests your ability to solve layered problems using nested logic.

Common Scenarios: Filtering based on average metrics, selecting values within conditions.

Key Techniques:

• Subqueries in WHERE, IN, NOT IN, EXISTS

• Correlated vs. uncorrelated subqueries

• Derived tables

Practice Tip with AI2sql: Try, "Find employees with salaries above their department's average."

5. How to Rank Results

Why it's asked: Ranking appears in many performance-related business questions.

Common Scenarios: Top-performing products, highest revenue clients, etc.

Key Techniques:

• RANK(), DENSE_RANK(), and ROW_NUMBER() with OVER (ORDER BY ...)

• PARTITION BY to rank within categories

Practice Tip with AI2sql: Ask, "Rank products by total sales" or "Top 3 students per class by grade."

6. How to Find Gaps in Dates or Sequences

Why it's asked: Advanced logic test involving comparisons between rows.

Common Scenarios: Missing invoice numbers, gaps in logins or timestamps.

Key Techniques:

• LAG() or LEAD() to compare rows

• Self-joins with offset comparisons

• Generating complete sequences for comparison

Practice Tip with AI2sql: Ask, "Find missing login dates" or "Identify gaps in invoice numbers."

7. How to Pivot Data in SQL

Why it's asked: Pivoting is essential for reporting and dashboard readiness.

Common Scenarios: Displaying monthly metrics in columns, showing survey response breakdowns.

Key Techniques:

• Conditional aggregation with CASE WHEN

• PIVOT operator (if supported by SQL dialect)

Practice Tip with AI2sql: Try, "Show monthly sales per product with months as columns."

Leveraging AI2sql for Interview Preparation

While it's crucial to understand core SQL principles, tools like AI2sql can help you:

• Translate Your Thoughts: Input a data need in natural language and see how it becomes SQL.

• Understand Complex Queries: Paste complex questions into AI2sql to receive explanations.

• Explore Alternative Solutions: Get one version of a query and brainstorm others for comparison.

• Save Time on Repetitive Syntax: Focus your practice on logic, not boilerplate.

• Generate Practice Questions: Use AI2sql to simulate realistic interview-style SQL scenarios.

Conclusion

Nailing your SQL interview comes down to understanding core concepts and practicing them extensively. By focusing on these seven key areas — finding duplicates, calculating running totals, joining tables, using subqueries, ranking results, finding gaps, and pivoting data — you'll be well-prepared for a wide range of technical questions.

And with tools like AI2sql, you can supercharge your prep by getting instant feedback, exploring different techniques, and reinforcing your learning with real-world examples.

Good luck — and happy querying!

👉 Try AI2sql for free and start practicing smarter!