SQL Basics

The spreadsheet that broke

A marketing team at a mid-size SaaS company tracked everything in spreadsheets. Customer data, campaign results, revenue — all in interconnected Google Sheets. It worked when they had 500 customers.

Then they hit 50,000 customers. The spreadsheets froze, crashed, and gave wrong answers because formulas broke when rows were added. Reports that took 10 minutes now took 2 hours. Nobody trusted the numbers.

The fix wasn't a bigger spreadsheet. It was a database — and SQL to talk to it. Within a month, the same reports ran in seconds. Queries that would have taken an analyst all day took 3 lines of SQL.

What SQL actually is

SQL (Structured Query Language, pronounced "sequel" or "S-Q-L" — both are correct) is a language for managing and querying data stored in relational databases.

A relational database is just organized tables — like spreadsheets, but with superpowers:

The key concepts

Your first SQL queries

SELECT — Getting data

The most fundamental command. "Show me this data."

SELECT name, email, signup_date
FROM customers;

This says: "From the customers table, show me the name, email, and signup_date columns." That's it.

Want everything? Use *:

SELECT * FROM customers;

WHERE — Filtering data

"Show me this data, but only rows that match a condition."

SELECT name, email
FROM customers
WHERE country = 'United States';

You can combine conditions:

SELECT name, email, total_spent
FROM customers
WHERE country = 'United States'
  AND total_spent > 100
  AND signup_date > '2025-01-01';

ORDER BY — Sorting results

SELECT name, total_spent
FROM customers
ORDER BY total_spent DESC;

DESC = descending (highest first). ASC = ascending (lowest first, default).

LIMIT — Capping results

SELECT name, total_spent
FROM customers
ORDER BY total_spent DESC
LIMIT 10;

"Show me the top 10 customers by spending."

Aggregating data

This is where SQL gets powerful — summarizing thousands of rows into useful numbers.

COUNT, SUM, AVG, MIN, MAX

-- How many customers do we have?
SELECT COUNT(*) FROM customers;

-- What's our total revenue?
SELECT SUM(amount) FROM orders;

-- What's the average order value?
SELECT AVG(amount) FROM orders;

-- What's the biggest single order?
SELECT MAX(amount) FROM orders;

GROUP BY — Aggregating by category

"Show me the total revenue broken down by country."

SELECT country, SUM(amount) as total_revenue, COUNT(*) as order_count
FROM orders
GROUP BY country
ORDER BY total_revenue DESC;

This is the equivalent of a pivot table — but faster and reproducible.

JOINs — Combining tables

Real databases have multiple related tables. JOINs connect them.

Imagine two tables:

• customers — id, name, email
• orders — id, customer_id, product, amount

To see customer names with their orders:

SELECT customers.name, orders.product, orders.amount
FROM orders
JOIN customers ON orders.customer_id = customers.id;

This "joins" the two tables on the matching IDs. Every analyst uses JOINs daily.

Real-world SQL use cases

Getting started today

Key takeaways

• SQL is how you query databases — the most in-demand data skill across all industries
• SELECT gets data, WHERE filters it, GROUP BY summarizes it, JOIN connects tables
• Aggregate functions (COUNT, SUM, AVG) turn thousands of rows into useful numbers
• SQL appears in over half of data job postings and 58.6% of developers use it regularly (Stack Overflow Developer Survey, 2023)
• You can learn the core commands in a weekend with free browser-based tools
• Every role that touches data benefits from SQL — marketing, product, finance, engineering