How to Use Google BigQuery to Practice SQL for Free

Want to practice SQL without installing anything or spending a dime? With Google BigQuery Sandbox, you can explore real datasets, write queries online, and build your SQL skills for free  –  no credit card required. This guide will show you how to get started step by step.

What is Google BigQuery?

Google BigQuery is a cloud-based data warehouse  –  a type of database made for storing and analyzing large amounts of data. It’s built by Google and is part of Google Cloud. You use SQL to search, filter, and analyze the information stored in it.

BigQuery is beginner-friendly because you don’t need to manage any servers, and it gives you access to free public datasets you can explore and practice with right away. You can start using it with just a free Google account  –  no credit card required. If you want to try more advanced features, Google also gives you $300 in free credits when you sign up for Google Cloud.

BigQuery is a great way to get hands-on experience with SQL in a real-world, cloud-based environment. You can query interesting datasets directly in your browser  –  no setup or installations needed. It’s a practical, low-barrier entry point for anyone learning SQL or curious about working with cloud data tools.

If you're new to SQL, a great way to start is with the SQL Basics course. It’s an interactive, beginner-friendly course that will help you build a strong foundation  –  perfect before diving into BigQuery.

What is BigQuery Sandbox?

Google BigQuery Sandbox is a free version of BigQuery that allows you to try it out without adding a credit card. It’s perfect for beginners who want to learn how to work with data, write SQL queries, or explore public datasets. You can store up to 10 GB of data and run up to 1 TB of queries each month for free. The sandbox gives you most of the main features of BigQuery, but any tables you create will automatically be deleted after 60 days. It’s a great option if you want to practice or test things without worrying about costs.

How to Set Up Your Google BigQuery Sandbox

Here are the steps to set up your free BigQuery account:

1. Create a Google account or sign-up to your existing Google account.
2. Go to BigQuery Console directly: https://console.cloud.google.com/bigquery. (Don’t Google “BigQuery”  –  that will take you to a marketing page instead of the console.)
3. Create a new project Google Cloud or select an existing project.
4. If needed, enable the BigQuery API in your project.

After these steps, you’ll land in the BigQuery interface. It should look something like this:

First Steps in BigQuery Sandbox

BigQuery Studio welcomes you with a starting screen. Click "Open query" to see an example query using one of the public datasets.

You’ll also see a short visual guide you can click through, if you’d like. It’s a helpful way to understand the interface.

Then you’ll see a query editor with a sample SQL query already loaded. Click the “Run” button above the editor to execute the query. The results will appear in the “Query results” panel below.

Add Public Datasets to Your Project

A great place to start is with Google’s free public datasets. Click the link below to open the bigquery-public-data project: https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=samples&page=dataset

Make sure to star the dataset for easier access later.

Explore the datasets in this project – you’ll find sample data from topics like moon phases, or Wikipedia, and more. When you click on a dataset, you’ll see an overview of what it includes.

When you click on a table in the dataset, you’ll see more details:

• Schema –  shows column names and data types.
• Details –  describes the table or dataset.
• Preview –  lets you see a sample of the data.

You can also click "Query" to open a new query editor with that table already referenced  –  a great way to start writing your own queries quickly.

Ideas for Exploration

Once you're set up in BigQuery Sandbox, you can start exploring real-world data using SQL. Here are some interesting public datasets you can play with  –  and a few example questions you can try to answer with your queries.

⚾ bigquery-public-data.baseball

This dataset includes detailed data from Major League Baseball (MLB), including information about players, teams, games, and performance stats across different seasons.

Questions to explore:

• Which players hit the most home runs in a given season?
• What’s the average number of runs scored per game by each team?
• Which pitchers had the most strikeouts?

📰 bigquery-public-data.bbc_news

This dataset includes news articles from the BBC, organized by category and content. It’s great for practicing text filtering, grouping, and counting.

Questions to explore:

• How many articles were published for each category (e.g., politics, tech, business)?
• What are the most common words used in sports-related articles?
• Which categories have the highest number of articles?

🚓 bigquery-public-data.chicago_crime

This dataset has detailed crime data from the City of Chicago, updated weekly. It includes crime types, locations, and timestamps.

Questions to explore:

• What are the most common types of crime in Chicago?
• Which areas have the highest number of reported incidents?
• Is there a particular time of day when crimes are more likely to happen?

🌝 bigquery-public-data.moon_phases

This is a fun dataset that tracks moon phases by date. It’s great for practicing with dates, filtering, and joining with other data.

Questions to explore:

• On which dates did a full moon occur in 2023?
• How often does a new moon happen?
• What’s the average moon illumination per month?

🐍 bigquery-public-data.pypi

This dataset contains data from PyPI (Python Package Index)  –  the official third-party software repository for Python. You can explore downloads and release activity.

Questions to explore:

• What are the most downloaded Python packages?
• Which packages have had the most frequent updates?
• How many new packages were published each month in the past year?
  

These datasets give you a great chance to practice writing real SQL queries. You can use SELECT, GROUP BY, ORDER BY, COUNT, and even functions like DATE_TRUNC() or STRING_CONTAINS() to find interesting answers. No need to build your own database  –  just pick a topic you like and start querying!

Additional Resources

If you're just getting started with SQL and BigQuery, here are a few helpful resources to keep learning and practicing:

• 📄 SQL Basics Cheat Sheet – A quick reference for common SQL commands and syntax.
• 📘 BigQuery SQL Syntax Reference – Official Google documentation for BigQuery’s SQL syntax.

If you want to go beyond the basics and learn SQL step by step  –  or if you're a data analyst looking to strengthen your SQL skills  –  we recommend the All Forever SQL Package from LearnSQL.com. It gives you lifetime access to all interactive SQL courses, from beginner to advanced, so you can learn at your own pace and build real, practical skills.