SQL Tutorial for Beginners 2026

-- Select all columns from a table
SELECT * FROM users;

-- Select specific columns
SELECT name, email FROM users;

-- Use aliases
SELECT name AS full_name, age AS years
FROM users;

-- Unique values
SELECT DISTINCT country FROM users;

-- Limit results
SELECT * FROM users LIMIT 10;

-- Common beginner dataset:
-- users (id, name, email, country, age)
-- orders (id, user_id, amount, status, created_at)
-- products (id, name, price, category)

-- Basic WHERE
SELECT * FROM users WHERE country = 'India';

-- Multiple conditions
SELECT * FROM users
WHERE country = 'India' AND age > 25;

-- IN for a list of values
SELECT * FROM users
WHERE country IN ('India', 'USA', 'UK');

-- BETWEEN for a range
SELECT * FROM orders
WHERE amount BETWEEN 100 AND 500;

-- LIKE for pattern matching
SELECT * FROM users WHERE name LIKE 'A%';  -- starts with A
SELECT * FROM users WHERE name LIKE '%a';  -- ends with a
SELECT * FROM users WHERE name LIKE '%ok%'; -- contains ok

-- Sorting (default ASC)
SELECT name, age FROM users ORDER BY age DESC;

-- Multiple sort keys
SELECT * FROM users ORDER BY country ASC, age DESC;

-- Combine filter + sort + limit
SELECT name, age FROM users
WHERE country = 'India'
ORDER BY age DESC
LIMIT 5;

-- INNER JOIN (only matching rows)
SELECT u.name, o.amount
FROM users u
INNER JOIN orders o ON o.user_id = u.id;

-- LEFT JOIN (all users, plus matching orders)
SELECT u.name, o.amount
FROM users u
LEFT JOIN orders o ON o.user_id = u.id;

-- Find users with no orders
SELECT u.name
FROM users u
LEFT JOIN orders o ON o.user_id = u.id
WHERE o.id IS NULL;

-- Multiple JOINs
SELECT u.name, o.amount, p.name AS product
FROM users u
JOIN orders o ON o.user_id = u.id
JOIN products p ON p.id = o.product_id;

-- Self-join (employees + managers)
SELECT e.name AS employee, m.name AS manager
FROM employees e
LEFT JOIN employees m ON e.manager_id = m.id;

-- Count rows
SELECT COUNT(*) FROM users;

-- Sum + average
SELECT SUM(amount) AS total, AVG(amount) AS avg
FROM orders;

-- Group by one column
SELECT country, COUNT(*) AS user_count
FROM users
GROUP BY country;

-- Group by with filter inside
SELECT status, SUM(amount) AS revenue
FROM orders
WHERE created_at >= '2026-01-01'
GROUP BY status;

-- HAVING filters grouped results
SELECT country, COUNT(*) AS user_count
FROM users
GROUP BY country
HAVING COUNT(*) > 100;

-- Group + join combo (super common)
SELECT u.country, SUM(o.amount) AS revenue
FROM users u
JOIN orders o ON o.user_id = u.id
GROUP BY u.country
ORDER BY revenue DESC;

-- Remember:
-- WHERE → filters rows before grouping
-- HAVING → filters groups after aggregation

-- Scalar subquery (single value)
SELECT name FROM users
WHERE age > (SELECT AVG(age) FROM users);

-- Subquery in FROM
SELECT country, avg_age
FROM (
  SELECT country, AVG(age) AS avg_age
  FROM users
  GROUP BY country
) AS country_stats
WHERE avg_age > 30;

-- CTE (Common Table Expression) — readable alternative
WITH country_stats AS (
  SELECT country, AVG(age) AS avg_age
  FROM users
  GROUP BY country
)
SELECT * FROM country_stats WHERE avg_age > 30;

-- Multiple CTEs
WITH active_users AS (
  SELECT * FROM users WHERE status = 'active'
),
user_revenue AS (
  SELECT user_id, SUM(amount) AS revenue
  FROM orders
  GROUP BY user_id
)
SELECT a.name, r.revenue
FROM active_users a
JOIN user_revenue r ON r.user_id = a.id
ORDER BY r.revenue DESC;

-- Rule of thumb:
-- CTEs are the modern way to structure complex queries.
-- Prefer CTEs over nested subqueries for readability.

-- ROW_NUMBER: unique row number per partition
SELECT name, country,
  ROW_NUMBER() OVER (PARTITION BY country ORDER BY age DESC) AS rn
FROM users;

-- RANK: allows ties
SELECT name, score,
  RANK() OVER (ORDER BY score DESC) AS rank
FROM exam_results;

-- Get top 3 per country (super common pattern)
WITH ranked AS (
  SELECT name, country, salary,
    ROW_NUMBER() OVER (PARTITION BY country ORDER BY salary DESC) AS rn
  FROM employees
)
SELECT * FROM ranked WHERE rn <= 3;

-- LAG: previous row's value
SELECT date, revenue,
  LAG(revenue) OVER (ORDER BY date) AS prev_day_revenue
FROM daily_revenue;

-- Running total
SELECT date, revenue,
  SUM(revenue) OVER (ORDER BY date) AS running_total
FROM daily_revenue;

-- Moving average (last 3 days)
SELECT date, revenue,
  AVG(revenue) OVER (ORDER BY date ROWS 2 PRECEDING) AS ma_3
FROM daily_revenue;

-- Notes:
-- Window functions keep all rows (unlike GROUP BY).
-- PARTITION BY = "group by" for windows.
-- ORDER BY inside OVER = how to sequence rows.
-- These are heavily tested in data analyst interviews.

Free SQL Practice Platforms:

1. LeetCode (Database section)
   - Beginner to advanced problems
   - Great for interview prep

2. SQLBolt (sqlbolt.com)
   - Interactive lessons + exercises
   - Perfect for absolute beginners

3. HackerRank (SQL track)
   - Structured beginner track
   - Certification available

4. Mode Analytics SQL Tutorial
   - Real datasets, guided walkthroughs
   - Focus on analytics queries

5. StrataScratch (free tier)
   - Real interview questions
   - Good for advanced practice

6. DB-Fiddle
   - Browser-based SQL editor
   - No setup — just paste and run

Public Datasets to Practice On:

1. Kaggle Datasets
   - Thousands of real datasets (CSV → SQLite)
   - Start with small ones (< 10k rows)

2. Google BigQuery public data
   - NY taxi rides, GitHub repos, etc.
   - Free tier allows real-scale practice

3. Chinook Database
   - Classic example DB (music store)
   - Great for JOINs + aggregations

4. Northwind Database
   - Old but excellent for classic SQL practice
   - Covers orders, customers, products

5. Sakila Database
   - Movie rental DB with complex relationships
   - Great for JOIN practice

Download CSV, load into DB, practice:
- DB Browser for SQLite (free, cross-platform)
- pgAdmin (PostgreSQL)
- MySQL Workbench
- DBeaver (any database)

Local Practice Setup (5 minutes):

Option 1: SQLite (simplest)
- Install DB Browser for SQLite
- Open a .db file
- Run queries instantly
- No server setup needed

Option 2: PostgreSQL (industry standard)
- Install PostgreSQL
- Create a database
- Load a CSV with \copy
- Practice real-world SQL

Option 3: MySQL
- Install MySQL Community Server
- Use MySQL Workbench
- Very common in production

Option 4: Cloud (no install)
- Google BigQuery (free tier)
- AWS Athena (pay per query)
- Supabase (free Postgres)

Recommendation for beginners:
- Start with SQLite (no setup)
- Move to PostgreSQL once comfortable
- Both teach the same SQL fundamentals