Essential SQL Concepts You Must Know (With Examples)

Whether you're preparing for SQL interviews or building robust real-world applications, mastering these SQL fundamentals is non-negotiable.

This guide breaks down the core SQL concepts you need to know, with simple examples and real-life relevance.

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1. Databases & Tables

• A database stores structured data.

• A table organizes data into rows (records) and columns (fields).

Think of a table like an Excel sheet — each column has a specific data type, and each row is a data record.

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2. SQL Syntax Basics

SELECT column1, column2 
FROM table_name 
WHERE condition;

• SELECT: Fetch data

• FROM: Specify the table

• WHERE: Apply filters and conditions

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3. Data Types

• INT, FLOAT, DECIMAL — Numeric data

• VARCHAR, TEXT — Strings

• DATE, DATETIME, TIME — Date/Time

• BOOLEAN — True/False

• NULL — Unknown or missing value

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4. Filtering Data

SELECT * FROM users 
WHERE age > 25 AND city = 'Mumbai';

🛠️ Use logical operators like:

• AND, OR, NOT

• IN, LIKE, BETWEEN, IS NULL

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5. Sorting & Limiting

SELECT * FROM orders 
ORDER BY amount DESC 
LIMIT 5;

Sort data using ORDER BY and control the result count with LIMIT.

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6. Aggregate Functions

• COUNT() — Number of rows

• SUM() — Total sum

• AVG() — Average

• MAX() / MIN() — Highest/Lowest

SELECT department, AVG(salary) 
FROM employees 
GROUP BY department;

Used mostly with GROUP BY.

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7. Joins (Combining Tables)

SELECT e.name, d.name 
FROM employees e 
JOIN departments d ON e.dept_id = d.id;

• INNER JOIN — Matching records from both tables

• LEFT JOIN — All from left + matched from right

• RIGHT JOIN, FULL OUTER JOIN — Other combinations

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8. Subqueries

SELECT name 
FROM users 
WHERE id IN (SELECT user_id FROM orders);

Subqueries are queries inside another query.

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9. Set Operations

• UNION — Combine unique results

• UNION ALL — Includes duplicates

• INTERSECT, EXCEPT — Set comparisons

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10. Constraints

Constraints enforce data rules.

• PRIMARY KEY — Uniquely identifies a row

• FOREIGN KEY — References another table

• UNIQUE, NOT NULL, DEFAULT, CHECK — Additional controls

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11. Views

CREATE VIEW top_customers AS 
SELECT name, SUM(amount) AS total 
FROM orders 
GROUP BY name;

Views are virtual tables created from queries — useful for reporting or hiding complex logic.

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12. Indexes

CREATE INDEX idx_name ON employees(name);

Indexes boost query performance, especially on large datasets.

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13. Transactions & ACID Properties

START TRANSACTION;
-- your SQL statements
COMMIT; -- or ROLLBACK;

Transactions group multiple steps into one unit.

✅ ACID stands for:

• Atomicity — All or nothing

• Consistency — Valid data only

• Isolation — No interference

• Durability — Changes persist

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14. Window Functions

SELECT name, salary, 
       RANK() OVER (ORDER BY salary DESC) AS rank 
FROM employees;

Window functions perform calculations across a set of rows without collapsing the result (unlike aggregates).

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15. Normalization

Normalization = Breaking larger tables into smaller ones to eliminate redundancy and ensure data integrity.

Forms include:

• 1NF – Atomic columns

• 2NF – Remove partial dependencies

• 3NF – Remove transitive dependencies

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Learning SQL isn't just about writing queries—it's about thinking in data. These concepts form the foundation of every backend system, BI tool, and data-driven app.

Bookmark this article for your daily SQL revision.
Keep practicing. Build queries. Break them. Learn by doing.

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✍ Written by Rishabh Mishra