SQL Cheat Sheet for Data Scientists Part- 2

A practical SQL reference covering queries, joins, aggregations, CTEs, window functions, NULL handling, dates, ranking, and common interview patterns.

SQL is one of the most important skills for a Data Scientist.

You may build sophisticated machine-learning models in Python, but before modeling begins, you often need to answer much simpler questions:

Where is the data?

How do I filter it?

How do I combine tables?

How do I calculate business metrics?

How do I find duplicates, trends, rankings, or missing information?

That is where SQL becomes essential.

This cheat sheet focuses on the SQL concepts and patterns worth remembering for Data Science interviews and practical work.

1. Basic SELECT

Suppose we have:

employees

employee_id
name
department
salary
experience
joining_date

Retrieve everything:

SELECT *
FROM employees;

Retrieve selected columns:

SELECT name, salary
FROM employees;