10 SQL Queries Every Data Analyst Must Know

SQL is the backbone of data analytics. Whether you're pulling reports, analysing trends, or cleaning data, these 10 patterns cover 80% of what you need on the job every single day.

1. SELECT with Filters

The most fundamental pattern. Always filter early to reduce data volume.

SELECT customer_name, order_value, order_date
FROM orders
WHERE order_date >= '2026-01-01'
  AND order_value > 1000
ORDER BY order_value DESC;

2. GROUP BY with Aggregations

Aggregations are the bread and butter of reporting. Combine GROUP BY with SUM, COUNT, AVG.

SELECT product_category,
  COUNT(*) AS total_orders,
  SUM(revenue) AS total_revenue,
  ROUND(AVG(revenue), 2) AS avg_order
FROM sales
GROUP BY product_category
ORDER BY total_revenue DESC;

3. JOINs for Combining Tables

Real data lives in multiple tables. INNER JOIN, LEFT JOIN, and multi-table joins are critical to master.

SELECT o.order_id, c.customer_name, p.product_name
FROM orders o
INNER JOIN customers c ON o.customer_id = c.id
LEFT JOIN products p ON o.product_id = p.id
WHERE o.status = 'completed';