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10 Portfolio-Ready SQL Projects for All Levels

Select your first—or next—SQL project to practice your current SQL skills, develop new ones, and create an outstanding professional portfolio.
Aug 2023  · 11 min read

SQL is a must-have skill for any aspiring data practitioner. Many modern companies store vast amounts of their data in various tables of relational databases. To extract the necessary data from a database for further manipulation and data analysis, you must have a good grasp of SQL.

Building SQL projects can benefit you in at least three ways:

  1. Practice your current SQL skills
  2. Develop new skills
  3. Build your data portfolio to showcase your SQL skills to potential employers.

This article will discuss several ideas for portfolio-ready SQL projects. Whether you're a beginner in SQL or a more advanced practitioner, you'll find various interesting topics to explore.

SQL Projects for Beginners

If you're already familiar with the basic SQL concepts, you're ready for your first SQL project. Make sure you have the following skills:

  • Performing mathematical operations
  • Aggregating and describing data (minimum, maximum, average, count, and sum)
  • Filtering data based on a certain condition or several conditions
  • Grouping data
  • Ordering data
  • Limiting the output data
  • Simple record joining (inner joins)
  • Aliasing columns or tables

For a quick refresh, take a look at our SQL Basics Cheat Sheet.

At the very beginning, it's totally fine to complete simple, single-task data manipulation projects. You can always improve and expand on such projects later when you gain more SQL knowledge and acquire new skills.

1. Analyzing industry carbon emissions

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In the Analyzing Industry Carbon Emissions project, you'll use the available dataset about product carbon emissions (that make up more than 75% of global emissions and represent a serious ecological problem) to explore the carbon footprint of various industries from the most recent year and determine the highest emitting industries.

While this is an introductory single-task project, you may need to go through the lessons of the Intermediate SQL course: Summarizing subsets and Filtering grouped data.

2. Analyzing students' mental health in SQL

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In the Analyzing Students' Mental Health in SQL project, you'll use your PostgreSQL skills to analyze the student data from a Japanese international university and spot one of the most influencing factors impacting the mental health of international students.

The survey conducted by the university demonstrated that the main challenges for international students are social connectedness and the stress associated with joining a new culture. Your particular task for this beginner SQL project will be to focus on a specific contributing factor—the length of stay and how it impacts the average diagnostic scores of international students.

3. Analyzing motorcycle part sales

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In the Analyzing Motorcycle Part Sales SQL project, you'll dig into the data of a company that sells motorcycle parts to get insights about their wholesale sales over time across three warehouse sites and help them understand their revenue streams. More precisely, you'll determine how much net revenue the company generates across its product lines by month and warehouse.

For this project, you'll also need solid reporting skills alongside your SQL skills. The course Data-Driven Decision Making in SQL can help you upskill in this area.

Intermediate SQL Projects

While building short single-task SQL projects is a good start, at some time on your learning journey, you'll reach the point when you'll want to create something more exciting and explore the data from many angles. The good news is that for such multi-task projects, having the same essential SQL skills listed at the beginning of the previous chapter is still enough.

4. What and where are the world's oldest businesses?

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In the What and Where are the World's Oldest Businesses SQL project, you'll examine the data from BusinessFinancing.co.uk to discover the oldest businesses in the world—those that survived changing market conditions for hundreds of years and are still operating. You're going to obtain a lot of curious findings:

  • The range of the founding years of the oldest companies in the world
  • The oldest company in the world and the industry it belongs to
  • How many companies—and which ones—were founded before 1000 AD
  • The most common industries to which the oldest companies belong to
  • The oldest companies by continent
  • The most common industries for the oldest companies on each continent

Since the data for this intermediate SQL project is contained in several different database tables, for many tasks, you'll need to use joining techniques to merge the necessary data for many tasks. You can refer to the Joining Data with SQL course to learn how to do it.

5. Analyzing NYC public school test result scores

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In the Analyzing NYC Public School Test Result Scores project, you'll work with a SQL database containing the SAT (Scholastic Aptitude Test) scores from New York City's public schools to determine test performance across those schools. You'll look at the following aspects:

  • How many schools fail to report information
  • Which (or how many) schools are best/worst in each of the three components of the SAT—reading, math, and writing
  • The best/worst scores for different SAT components
  • The top 10 schools by average total SAT scores
  • How the test performance varies by borough
  • The top 5 schools by average SAT scores across all three components (or for a certain component) for a selected borough

Whenever you have doubts about which command to use (and how to use it) in each particular case for this intermediate SQL project, feel free to check this comprehensive tutorial—SQL Commands for Data Scientists.

6. Analyze international debt statistics

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In the Analyze International Debt Statistics project, you'll investigate international debt data collected by The World Bank, a global organization that funds countries to manage their economies. You're going to reveal some interesting facts and figures, including:

  • The number of countries with debt
  • The total amount of debt owed by all the countries
  • The country with the highest debt and the amount of its debt
  • The average amount of debt owed by countries across different debt indicators
  • The most common debt indicator

SQL Projects for Advanced Level

To proceed with more advanced SQL projects that can effectively help you stand out of the crowd, you should be comfortable with more advanced techniques in addition to the essential ones listed in the first section. Check if you know how to do the following things in SQL:

  • Using all kinds of joins (including self joins)
  • Matching and extracting patterns
  • Dealing with the if/then/else logic in SQL
  • Creating views
  • Creating complex nested queries
  • Using common table expressions
  • Applying SQL window functions
  • Truncating data
  • Labeling data
  • Applying set operators
  • Working with dates and times

7. Analyzing unicorn companies

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In the Analyzing Unicorn Companies project, your task will be to figure out how many companies reached a valuation of over 1 billion dollars across different industries in a given time period.

Specifically, you'll need to identify the three best-performing industries based on the number of new high-growth companies created in that period, find the number of unicorns that emerged within these industries by year, the year when each of those companies became a unicorn, and their average valuation in billions of dollars. And all this information you can obtain in just one query!

For this project, you're going to use a PostgreSQL database containing several tables. For a refresh on some key skills, you can find these courses: Functions for Manipulating Data in PostgreSQL and Cleaning Data in PostgreSQL Databases.

8. Optimizing online sports retail revenue

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In the Optimizing Online Sports Retail Revenue project, you'll dive into product data for an online sports clothing company with the final goal of developing recommendations for the company to maximize its revenue. You will deal with a wide variety of information kept in several tables. The information includes prices, discounts, revenue, ratings, reviews, product descriptions, and website traffic. You're going to answer questions like:

  • How do the price points of Nike and Adidas products differ?
  • Is there a difference in the amount of discount offered between the brands?
  • Is there any correlation between revenue and reviews? And if so, how strong is it?
  • Does the length of a product's description influence a product's rating and reviews?
  • Are there any trends or gaps in the volume of reviews by month?
  • How much of the company's stock consists of footwear items? What is the median revenue generated by these products?
  • How does footwear's median revenue differ from clothing products?

In this project, you'll need to apply advanced SQL skills such as aggregation, summarizing, truncating, cleaning, labeling, casting, common table expressions, correlation, and working with dates and times. All these techniques are covered in the Exploratory Data Analysis in SQL course.

9. When was the golden age of video games?

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In the When Was the Golden Age of Video Games? SQL project, you'll analyze the top 400 best-selling video games released since 1977 to identify whether or not the gaming market has improved with time and when its most flourishing epoch was. For this purpose, you'll work with video game release years, critic and user scores, and sales data. You're going to search for the following insights:

  • The top 10 best-selling video games of all time and the period they were released
  • The top 10 years with the highest average critic scores and many hits produced
  • The top 10 years with the highest average user scores and many hits produced
  • The years with the highest average scores from both critics and players and many hits produced
  • The number of games sold in those years

To perform the above tasks for this SQL project for advanced users, you'll need to use various kinds of joins and set operators, so make sure you brush up on these skills with the SQL Joins Cheat Sheet.

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In the Analyzing American Baby Name Trends project, you'll study data provided by the U.S. Social Security Administration containing first names, which were given to over 5,000 American babies each year for the period of 101 years. The main goal is to understand how American baby name tastes changed by investigating trends of popularity. In particular, you're going to discover:

  • Classic American names for over 100 years
  • The type of popularity for each name: timeless vs. trendy
  • The top 10 female names
  • The most popular female name ending in "a" since 2015
  • The most popular male names by year
  • The most popular male name for the largest number of years

For this advanced project, you can find helpful the Data Manipulation in SQL course.

Final Thoughts

In this article, we outlined various ideas for SQL projects for all levels of SQL competence. In addition, we overviewed the skills you'll need for each project and the learning resources for gaining and polishing them.

Now that you're fully ready to start building these SQL projects and growing your professional portfolio. It's never too early or too late to start mastering and showcasing your skills!

Once you have your portfolio of SQL projects ready to go, you’ll also want to brush up on the top SQL interview questions to make sure you impress potential employers at the interview stage.


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