Every Soma

SQL · Beginner

SQL for Data Analysis

Learn to query, aggregate, and analyze data with SQL through more than 100 hands-on exercises.

Price
$29
Level
Beginner
Duration
9 hours
Lessons
35 lessons
Projects
4 hands-on projects · 100+ exercises
Prerequisites
None — no programming experience required

Overview

SQL for Data Analysis is a 9-hour course that teaches you how to answer real questions with data stored in relational databases. Across 35 lessons, more than 100 exercises, and 4 projects, you progress from your first SELECT statement to analytical queries that combine multiple tables.

The course is exercise-driven: every concept is immediately practiced against realistic datasets. You learn to filter rows with WHERE, summarize data with GROUP BY and aggregate functions, combine tables with JOINs, and structure more complex logic with subqueries.

The final modules focus on the day-to-day work of a data analyst: cleaning messy data and writing analytical queries that turn raw tables into clear answers.

What you'll learn

  • Retrieve exactly the data you need with SELECT and WHERE
  • Summarize data with GROUP BY and aggregate functions
  • Combine tables with INNER, LEFT, and other JOINs
  • Structure complex questions with subqueries
  • Clean inconsistent and missing data directly in SQL
  • Write analytical queries that answer real business questions
  • Practice with more than 100 exercises on realistic datasets
  • Complete 4 analysis projects from question to answer

Curriculum

7 modules · 35 lessons · 9 hours of material

  1. Module 1 — Your First Queries

    • How relational databases organize data
    • SELECT: choosing columns
    • Sorting results with ORDER BY
  2. Module 2 — Filtering with WHERE

    • Comparison operators and conditions
    • AND, OR, and NOT
    • Pattern matching with LIKE
    • Handling NULL values
  3. Module 3 — Aggregation and GROUP BY

    • COUNT, SUM, AVG, MIN, and MAX
    • Grouping rows with GROUP BY
    • Filtering groups with HAVING
    • Project: sales summary report
  4. Module 4 — Joining Tables

    • Primary keys and foreign keys
    • INNER JOIN
    • LEFT JOIN and when to use it
    • Joining more than two tables
  5. Module 5 — Subqueries

    • Subqueries in WHERE
    • Subqueries in FROM
    • Correlated subqueries
  6. Module 6 — Data Cleaning in SQL

    • Standardizing text and dates
    • Dealing with duplicates
    • Handling missing values
    • Project: cleaning a messy orders table
  7. Module 7 — Analytical Queries

    • Translating questions into queries
    • Building multi-step analyses
    • Project: customer behavior analysis
    • Final project: end-to-end data analysis in SQL

Who this course is for

  • Beginners who want a practical first step into data work
  • Analysts who currently rely on spreadsheets and want to query databases directly
  • Marketers, product managers, and operations professionals who work with data
  • Developers who want a solid grounding in SQL for application work

Prerequisites

None — no programming experience required

Course outcomes

By the end of this course, you will be able to:

  • Write correct, readable SQL queries from scratch
  • Summarize and compare data across groups with confidence
  • Combine data from multiple tables to answer real questions
  • Complete an end-to-end analysis project entirely in SQL

Frequently asked questions

Is SQL hard to learn for a non-programmer?

SQL is one of the most approachable languages for non-programmers because it reads close to plain English. This course assumes no programming background and builds up gradually through more than 100 exercises.

Which database does the course use?

The course teaches standard SQL that applies across common databases such as PostgreSQL, MySQL, and SQLite. Differences between databases are pointed out where they matter.

Should I learn SQL or Python first?

For data analysis, SQL is often the fastest path to being useful with data. See the guide Python vs SQL: Which Should You Learn First? for a detailed comparison.

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