Intermediate SQL Queries for Data Analysis and Reporting Practice

SQL Queries for Practice




Introduction

As you move beyond the basics of SQL, the real learning begins with hands-on, problem-solving experiences. Intermediate-level queries are where you start to bridge the gap between knowing the syntax and actually analyzing data and generating reports that support business decisions. This guide focuses on intermediate SQL queries for practice, specifically designed to enhance your skills in data analysis and reporting.

Whether you're preparing for a job in data analysis, business intelligence, or backend development, building a solid routine of SQL practice with real-world queries is essential.


Why Practice Intermediate SQL Queries?

Once you’re comfortable with basic SELECT, WHERE, and JOIN statements, you need to start thinking like a data analyst. This means:

  • Extracting insights from raw data

  • Cleaning and filtering data

  • Performing calculations and aggregations

  • Creating reports using grouped data

  • Writing queries that answer business questions

Intermediate SQL queries give you this power. The best way to grow is by doing—and for that, you need SQL queries for practice that challenge and improve your skill set.


Core Concepts to Master at the Intermediate Level

Here are some of the key SQL skills that intermediate users should develop:

1. GROUP BY and Aggregate Functions

You should already know COUNT(), SUM(), AVG(), MAX(), and MIN(). Now start using them with GROUP BY to produce summary reports.

Example:

SELECT department, COUNT(*) AS total_employees, AVG(salary) AS avg_salary
FROM employees
GROUP BY department;

This gives you a report showing the number of employees and average salary by department.


2. HAVING Clause for Filtered Aggregates

The HAVING clause is like WHERE, but it's used to filter aggregated results.

SELECT customer_id, COUNT(order_id) AS total_orders
FROM orders
GROUP BY customer_id
HAVING COUNT(order_id) > 5;

This query returns customers with more than five orders.


3. Subqueries and Nested SELECTs

Subqueries allow you to compare or calculate data dynamically inside another query.

SELECT name, salary
FROM employees
WHERE salary > (
    SELECT AVG(salary)
    FROM employees
);

This gives you all employees who earn more than the average salary.


4. CASE Statements

CASE is SQL’s version of IF-THEN-ELSE, used to create conditional columns.

SELECT name, salary,
    CASE
        WHEN salary > 100000 THEN 'High'
        WHEN salary > 50000 THEN 'Medium'
        ELSE 'Low'
    END AS salary_bracket
FROM employees;

This is great for data categorization, which is common in reporting.


5. JOINs Across Multiple Tables

At this level, you should be comfortable with INNER JOIN, LEFT JOIN, and even FULL OUTER JOIN.

SELECT c.name, o.order_date, o.amount
FROM customers c
JOIN orders o ON c.customer_id = o.customer_id;

You’ll often need to pull data from multiple tables to answer real business questions.


6. Date Functions and Filtering

Business reporting often involves time-based metrics.

SELECT EXTRACT(YEAR FROM order_date) AS order_year, COUNT(*) AS total_orders
FROM orders
GROUP BY EXTRACT(YEAR FROM order_date);

This shows how many orders were placed each year.


Real-World SQL Practice Examples

Here are a few SQL queries for practice that simulate real-world reporting scenarios:

  • Top 5 products by revenue

SELECT product_id, SUM(quantity * price) AS revenue
FROM sales
GROUP BY product_id
ORDER BY revenue DESC
LIMIT 5;
  • Monthly active users (MAU)

SELECT DATE_TRUNC('month', login_date) AS month, COUNT(DISTINCT user_id) AS active_users
FROM user_logins
GROUP BY month;
  • Customer retention report

SELECT customer_id,
       MIN(order_date) AS first_order,
       MAX(order_date) AS last_order,
       COUNT(order_id) AS total_orders
FROM orders
GROUP BY customer_id
HAVING COUNT(order_id) > 1;

These types of queries mimic what you’d build as a data analyst for management reporting or dashboards.


Tools and Resources for Practicing SQL

Here are some ways to continue your SQL practice:

  • Online platforms: Try LeetCode, HackerRank, SQLZoo, Mode Analytics, or W3Schools for structured challenges.

  • Sample databases: Use open datasets like Sakila, Chinook, or Northwind to practice real queries.

  • Project-based learning: Build your own reporting dashboard using SQL and tools like Power BI or Tableau.


Best Practices for Intermediate SQL Users

  • Format your SQL: Use indentation and line breaks for better readability.

  • Use aliases: Name your tables and columns clearly when joining multiple tables.

  • Test incrementally: Start small, run your query, then add complexity step by step.

  • Validate data: Check row counts, NULL values, and outliers before trusting results.


Conclusion

Becoming proficient in SQL isn't about memorizing syntax—it's about applying it. With these SQL queries for practice, you’re not only reinforcing your technical knowledge but also learning how to think analytically and solve business problems using data. Intermediate-level SQL practice opens the door to complex reporting, data quality checks, and impactful insights.

So keep practicing, keep querying, and watch your confidence and capability grow with every report you build.



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