40 ChatGPT Prompts to Write SQL Queries Like a Pro
Introduction: The Smart Way to Write SQL in 2025
Whether you're pulling sales reports, analyzing customer behavior, or building a data pipeline for a U.S.-based SaaS product, SQL remains the backbone of database querying. But writing efficient, readable, and bug-free SQL queries takes time, especially when working with complex joins, nested queries, or unfamiliar schemas.
Enter ChatGPT, your AI-powered SQL assistant.
This guide will walk you through 40+ real-world ChatGPT prompts that developers, analysts, and engineers in the United States can use to write, troubleshoot, and optimize SQL queries for MySQL, PostgreSQL, SQL Server, and beyond.
These prompts aren’t generic they're actionable, detailed, and tuned for real USA-based business use cases like eCommerce, finance, healthcare, and SaaS analytics.
Why Use ChatGPT for Writing SQL Queries?
- Speed up repetitive queries
- Eliminate syntax errors
- Understand complex joins
- Convert English to SQL easily
- Improve performance through query optimization
With the right prompts, ChatGPT can become your SQL co-pilot whether you're building dashboards, running audits, or writing queries for your backend systems.
Prompts for Basic SQL Queries
Start with foundational operations like SELECT, WHERE, and ORDER BY.
1. “Write a SQL query to select all customers from the customers table where the country is ‘United States’.”
2. “Generate a SQL query that selects the top 10 products by revenue from the sales table.”
3. “Create a SQL statement that returns all rows from the employees table where the job title is 'Sales Manager' and the department is 'North America'.”
4. “Write a query to retrieve all orders placed in the last 30 days from the orders table.”
5. “Build a SQL query that returns the total number of users who signed up each month in the last year.”
Prompts for Aggregations and Grouping
Use these prompts for totals, averages, and grouped results.
6. “Generate a SQL query to count the number of orders per U.S. state from the orders table.”
7. “Write a query that shows the average order value by customer segment.”
8. “Build a SQL query to find the total revenue per product category for Q1 2025.”
9. “Create a SQL query that returns the maximum, minimum, and average order value for each store.”
10. “Write a grouped SQL query to show total new subscriptions per U.S. city in descending order.”
Prompts for JOIN Queries
Merge data from multiple tables with detailed join prompts.
11. “Write a SQL query that joins orders and customers to display customer names with their order totals.”
12. “Generate a LEFT JOIN query between employees and departments to show all employees and their department names.”
13. “Build a query to list all products along with their supplier name using an INNER JOIN.”
14. “Write a SQL query to find all U.S. customers who have not placed any orders using a LEFT JOIN and NULL filter.”
15. “Create a multi-table JOIN that links orders, order_items, and products to show a detailed order breakdown.”
Prompts for Filtering and Sorting
Fine-tune your results with WHERE, IN, BETWEEN, and ORDER BY.
16. “Generate a SQL query that selects all users who registered between January 1st and June 30th, 2025.”
17. “Write a query to return all products priced between $50 and $100, sorted by price descending.”
18. “Create a SQL statement that shows the top 5 customers by lifetime spend in the U.S.”
19. “Build a query to find all employees with the last name starting with ‘S’ in the employees table.”
20. “Generate a SQL query to find all orders with a ‘Pending’ or ‘In Progress’ status.”
Prompts for Subqueries and Nested Queries
Get advanced with subqueries that help you filter or calculate inside other queries.
21. “Write a SQL query that finds customers who spent more than the average customer.”
22. “Create a query to return products that have never been sold by checking against the order_items table.”
23. “Build a nested SQL query to find the highest-grossing product in each category.”
24. “Generate a query that lists employees who make more than their department’s average salary.”
25. “Write a subquery that returns customers with the most recent order in each state.”
Prompts for Date and Time Queries
Work with time zones, intervals, and date formatting.
26. “Write a SQL query to count the number of orders placed each weekday in the last 3 months.”
27. “Generate a SQL statement that converts UTC timestamps to EST.”
28. “Build a query that shows how many users registered per hour today.”
29. “Create a query to list inactive users who haven’t logged in for over 6 months.”
30. “Write a SQL query that shows revenue broken down by week for the last quarter.”
Prompts for Creating and Modifying Tables
Control database structure with DDL statements.
31. “Generate a SQL script to create a customers table with fields for ID, name, email, state, and created_at.”
32. “Write an ALTER TABLE statement to add a last_login column to the users table.”
33. “Create a SQL command to delete the test_users table if it exists.”
34. “Generate a script to add a foreign key to the orders table linking to customers.”
35. “Write a SQL statement to change a column data type from VARCHAR(50) to TEXT.”
Prompts for Query Optimization
Make your queries faster and more efficient.
36. “Rewrite this SQL query to use indexes and reduce full table scans.”
37. “Suggest optimizations for a JOIN query that’s taking more than 5 seconds to return results.”
38. “Generate a SQL EXPLAIN plan for a complex query and describe what each part means.”
39. “Write a version of this query that uses CTEs instead of subqueries for better readability.”
40. “Create a SQL query that paginates results using LIMIT and OFFSET for performance.”
Tips for Better SQL with ChatGPT
- Mention the database: “Write this for PostgreSQL” or “Format this for MySQL.”
- Include sample tables or schemas: ChatGPT can write better queries with context.
- Ask for explanations: Use prompts like, “Explain what this SQL query does.”
- Request variations: Follow up with “Now show this grouped by month instead of day.”
- Use real business context: ChatGPT performs better with domain-specific input like “U.S. subscription business” or “eCommerce inventory tracking.”
FAQs – Using ChatGPT for SQL Queries
Q1: Can ChatGPT handle complex SQL use cases like recursive queries?
Yes. You can prompt it to write recursive Common Table Expressions (CTEs), window functions, and nested logic across most SQL dialects.
Q2: Is it safe to use ChatGPT for production database queries?
It’s best to review and test all AI-generated SQL. While ChatGPT can write correct queries, edge cases and business rules still require human oversight.
Q3: Can I use these prompts with Snowflake, BigQuery, or Redshift?
Yes. You can specify the engine in your prompt for dialect-specific syntax and optimization.
Q4: Are these prompts suitable for learning SQL?
Absolutely. They’re great for hands-on practice and explanation-based learning, especially for students and junior developers in U.S. coding bootcamps or college courses.
Q5: Can ChatGPT help me debug a broken SQL query?
Definitely. Paste your query and ask: “Why is this not working?” or “Fix this query to return correct results.”
Final Thoughts: SQL + AI = Speed, Clarity, and Confidence
If you're writing SQL regularly whether you're a developer, data analyst, or product manager these prompts can drastically improve your speed, clarity, and confidence. Instead of struggling through nested logic or lengthy syntax, you're leveraging AI to build smarter.
For U.S. businesses, where time and data accuracy directly affect decisions, this workflow isn’t just convenient it’s strategic.
Want to write better SQL without the guesswork?
Use these 40+ ChatGPT prompts to master querying, optimize performance, and simplify your workflow. Whether you're working with eCommerce data in New York, healthcare records in Chicago, or fintech dashboards in San Francisco, these prompts are made for you.
