SQL Tutorial for Beginners India 2026
Learn SQL from Scratch for Data Analyst Jobs

What is SQL and Why Every Data Analyst in India Needs It

Your First SQL Query — SELECT and FROM

-- Retrieve all columns from the customers table
SELECT * FROM customers;

-- Retrieve specific columns only
SELECT customer_id, name, city, phone
FROM customers;

-- Give a column a readable alias (rename in output)
SELECT customer_id AS "Customer ID",
       name        AS "Customer Name",
       city        AS "City"
FROM customers;

Filtering Rows — WHERE Clause

-- Customers from Delhi only
SELECT name, city FROM customers
WHERE city = 'Delhi';

-- Orders above ₹50,000 placed in 2025
SELECT order_id, customer_id, amount, order_date
FROM orders
WHERE amount > 50000
  AND YEAR(order_date) = 2025;

-- Customers from Delhi OR Mumbai
SELECT name, city FROM customers
WHERE city IN ('Delhi', 'Mumbai', 'Noida');

-- Products with names starting with "Pro"
SELECT product_name, price FROM products
WHERE product_name LIKE 'Pro%';

-- Orders with no delivery date recorded yet
SELECT order_id FROM orders
WHERE delivery_date IS NULL;

Sorting Results — ORDER BY

-- Most expensive products first
SELECT product_name, price
FROM products
ORDER BY price DESC;

-- Customers alphabetically by city, then by name within each city
SELECT name, city FROM customers
ORDER BY city ASC, name ASC;

-- Top 5 largest orders
SELECT order_id, customer_id, amount
FROM orders
ORDER BY amount DESC
LIMIT 5;   -- use TOP 5 in SQL Server

Counting and Summarising — GROUP BY and Aggregate Functions

-- Total sales per city
SELECT city,
       SUM(amount) AS total_sales,
       COUNT(*)    AS order_count,
       AVG(amount) AS avg_order_value
FROM orders o
JOIN customers c ON o.customer_id = c.customer_id
GROUP BY city
ORDER BY total_sales DESC;

-- Cities with total sales above ₹10,00,000
SELECT city, SUM(amount) AS total_sales
FROM orders o
JOIN customers c ON o.customer_id = c.customer_id
GROUP BY city
HAVING SUM(amount) > 1000000;

-- Products sold fewer than 5 times (slow movers)
SELECT product_id, COUNT(*) AS times_sold
FROM order_items
GROUP BY product_id
HAVING COUNT(*) < 5;

Combining Tables — JOINs

-- INNER JOIN: orders with customer names (only orders with known customers)
SELECT o.order_id, c.name, c.city, o.amount
FROM orders o
INNER JOIN customers c ON o.customer_id = c.customer_id;

-- LEFT JOIN: all customers, including those with no orders
SELECT c.name, c.city, o.order_id, o.amount
FROM customers c
LEFT JOIN orders o ON c.customer_id = o.customer_id;

-- Customers who have NEVER placed an order
SELECT c.customer_id, c.name
FROM customers c
LEFT JOIN orders o ON c.customer_id = o.customer_id
WHERE o.order_id IS NULL;

-- Three-table JOIN: order + customer + product
SELECT o.order_id, c.name, p.product_name, oi.quantity, oi.unit_price
FROM orders o
JOIN customers   c  ON o.customer_id  = c.customer_id
JOIN order_items oi ON o.order_id     = oi.order_id
JOIN products    p  ON oi.product_id  = p.product_id;

Subqueries and CTEs — Multi-Step Queries

-- Find orders above the average order value
SELECT order_id, customer_id, amount
FROM orders
WHERE amount > (SELECT AVG(amount) FROM orders);

-- Find the second highest salary (classic interview question)
SELECT MAX(salary) AS second_highest
FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);

-- CTE version (cleaner for complex queries)
WITH avg_sales AS (
  SELECT city, AVG(amount) AS city_avg
  FROM orders o
  JOIN customers c ON o.customer_id = c.customer_id
  GROUP BY city
)
SELECT city, city_avg
FROM avg_sales
WHERE city_avg > (SELECT AVG(amount) FROM orders)
ORDER BY city_avg DESC;

Window Functions — The Advanced Skill That Gets You Hired

-- Rank employees by salary (highest = 1) within each department
SELECT name, department, salary,
  RANK() OVER (
    PARTITION BY department
    ORDER BY salary DESC
  ) AS salary_rank
FROM employees;

-- Running total of daily sales
SELECT sale_date, amount,
  SUM(amount) OVER (
    ORDER BY sale_date
    ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
  ) AS cumulative_sales
FROM daily_sales;

-- Month-over-month sales change using LAG
SELECT month, revenue,
  LAG(revenue) OVER (ORDER BY month) AS prev_month,
  revenue - LAG(revenue) OVER (ORDER BY month) AS change
FROM monthly_revenue;

-- Top 2 products per category (top-N-per-group — asked in interviews)
SELECT category, product_name, total_sales
FROM (
  SELECT category, product_name,
         SUM(amount) AS total_sales,
         ROW_NUMBER() OVER (
           PARTITION BY category
           ORDER BY SUM(amount) DESC
         ) AS rn
  FROM sales s
  JOIN products p ON s.product_id = p.product_id
  GROUP BY category, product_name
) ranked
WHERE rn <= 2;

How long does it take to learn SQL for a data analyst job in India?

With daily practice of 1–2 hours, most beginners can learn SQL well enough to clear a data analyst technical interview in 6–10 weeks. The basics — SELECT, WHERE, GROUP BY, and JOINs — take 2–3 weeks. Window functions and subqueries take another 3–4 weeks of consistent practice. What matters more than speed is depth — companies test whether you can write correct SQL under pressure, not just whether you know the syntax.

Which SQL database should a beginner learn first in India?

Start with MySQL or PostgreSQL — both are free, widely used, and teach the same core SQL syntax that transfers to SQL Server, Oracle, and BigQuery. MySQL is installed by millions of developers and has excellent beginner resources. PostgreSQL is increasingly preferred for its advanced features. Most Indian data analyst interviews test generic SQL that works across all databases — JOINs, GROUP BY, and window functions are the same in all major dialects.

Is SQL enough to get a data analyst job in India?

Strong SQL is the #1 skill for clearing technical interview rounds in India, but you also need Excel (for data manipulation and business reporting) and Power BI or Tableau (for visualisation). SQL + Excel + Power BI is the minimum toolkit for most data analyst roles in India in 2026. Python is increasingly asked for at mid-to-senior levels. SQL is the non-negotiable foundation — without it, you will not pass the technical round even if your other skills are strong.

What are the most important SQL concepts for data analyst interviews in India?

Indian data analyst interviews most commonly test: (1) JOINs — especially LEFT JOIN with IS NULL to find non-matching records; (2) GROUP BY with HAVING — aggregate queries with filtered groups; (3) Subqueries — particularly for "second highest salary" and "top N per group" problems; (4) Window functions — ROW_NUMBER(), RANK(), LAG() — tested at mid-level and above; (5) NULL handling — knowing that NULL = NULL is NULL and using IS NULL correctly. Practise these five areas and you will clear most Indian SQL interview rounds.