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5 Advanced SQL Interview Questions to Sharpen Your Skills
SQL is the backbone of data analysis and business intelligence, and mastering it can open doors to exciting opportunities. Over the years, I’ve guided aspiring data professionals and worked with clients to solve complex database challenges. Along the way, I’ve noticed that certain advanced SQL topics often separate the “good” from the “great” candidates in interviews.
In this post, I’m sharing 5 advanced SQL interview questions that I often encounter in real-world scenarios—perfect for practicing before your next interview or freelance project.
Table of Contents
1. Finding Duplicate Records in SQL
Imagine you’re working on a client’s sales database and notice repeated entries for the same transaction. Duplicate records can distort reports, KPIs, and dashboards.
A simple query to identify duplicates might look like this:
SELECT column_name, COUNT(*)
FROM table_name
GROUP BY column_name
HAVING COUNT(*) > 1;
This groups data and highlights values appearing more than once. As a consultant, I always emphasize clean data first, because even a perfect dashboard won’t save insights from dirty data!
2. Understanding Common Table Expressions (CTEs)
CTEs are like “mini queries” that make complex SQL statements readable and reusable. Think of them as temporary tables in your query.
Example:
WITH SalesCTE AS (
SELECT employee_id, SUM(sales_amount) AS total_sales
FROM sales
GROUP BY employee_id
)
SELECT * FROM SalesCTE WHERE total_sales > 10000;
I often use CTEs while tutoring advanced SQL, because they teach clarity in writing queries. It’s true what they say: “Clear code is like a well-cooked biryani—everyone enjoys it!”
3. Getting the Nth Highest Salary
A classic interview question is retrieving the 2nd, 3rd, or Nth highest salary. Here’s one way using ROW_NUMBER():
SELECT salary
FROM (
SELECT salary, ROW_NUMBER() OVER (ORDER BY salary DESC) AS rank
FROM employees
) AS ranked_salaries
WHERE rank = 2;
This is a practical skill I often use in client projects to rank employees, products, or customers, turning raw data into actionable insights.
4. Window Functions Explained
Window functions are a game-changer in SQL. Unlike aggregate functions that collapse rows, window functions let you perform calculations across sets of rows while keeping the original data intact.
Example—calculating cumulative sales:
SELECT
employee_id,
sales_date,
SUM(sales_amount) OVER (PARTITION BY employee_id ORDER BY sales_date) AS cumulative_sales
FROM sales;
I teach window functions regularly because they’re the Swiss knife of SQL analytics—perfect for ranking, running totals, moving averages, and cohort analysis.
5. Optimizing SQL Queries for Performance
Even the most elegant query can become a bottleneck with large datasets. Performance optimization is not just about speed; it’s about making insights available faster to decision-makers.
Some tips I follow and teach:
-
Use appropriate indexes on frequently filtered columns
-
Avoid
SELECT *; select only needed columns -
Break complex queries into smaller CTEs for readability and performance
-
Analyze execution plans to identify bottlenecks
As a freelancer and consultant, query optimization often saves clients hours of wait time and significantly improves dashboard performance.
Final Thoughts
Advanced SQL is not just about cracking interviews; it’s about solving real business problems efficiently. Whether you’re preparing for your next data analyst role, freelancing for a client, or just leveling up your skills, practicing these questions will give you a competitive edge.
If you’re serious about mastering SQL or want guidance on real-world analytics projects, feel free to reach out. I provide personalized tutoring and consultancy that bridges the gap between theory and practice.
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