10 Portfolio-Ready SQL Projects for All Levels

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

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

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. When was the golden age of video games?

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, 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.

4. Analyzing American baby name trends

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 may find the Data Manipulation in SQL course helpful.

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.

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

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
• 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. You can refer to the Joining Data with SQL course to learn how to do it.

6. Analyzing NYC public school test result scores

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.

7. Analyzing and formatting PostgreSQL Sales Data

In the Analyzing and Formatting PostgreSQL Sales Data project, you'll face a scenario that is all too common in the professional world: the data isn't ready for analysis yet. You will work with a "superstore" database where records have inconsistent formatting, incorrect data types, and missing values that threaten the accuracy of your reporting.

Your goal is to clean the dataset using PostgreSQL techniques to answer day-to-day retail business questions. Specifically, you will:

• Identify columns with incorrect data types (e.g., numbers stored as text) and convert them for calculation.
• Detect incomplete records and apply strategies to impute missing values for product quantities.
• Filter and aggregate the now-clean data to identify top-performing products.
• Analyze revenue trends that were previously hidden by data errors.

Since this project bridges the gap between raw data and actionable insights, it is an excellent way to practice the Data Cleaning in SQL skills that hiring managers prioritize.

SQL Projects for Advanced Level

To proceed with more advanced SQL projects that can effectively help you stand out from 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

8. Analyzing motorcycle part sales

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.

9. Analyzing unicorn companies

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.

10. Evaluate a manufacturing process

In the Evaluate a Manufacturing Process project, you'll step into the role of a Manufacturing Data Analyst. While consistency is key in production, operators often make adjustments to the machinery to improve efficiency. Your task is to analyze the data to determine if a recent change to the process improved quality or actually made it worse.

This project moves beyond simple "group by" statements and requires you to look at data trends over time. You will reveal critical insights such as:

• How quality metrics fluctuate across different production batches.
• Whether specific machinery adjustments correlate with a rise in defective products.
• The rolling average of product dimensions using advanced window functions.
• Standard deviation and variance in the manufacturing process to detect instability.

To successfully complete this project, you will need to be comfortable with Window Functions, Partitioning, and generating Summary Statistics. These are advanced concepts often tested in technical interviews for mid-to-senior roles.

Additional SQL Project Ideas

If you are still looking for additional SQL project ideas, consider something from this list.I think all of these project ideas are practically doable in SQL, butthe level of feasibility will depend on the dataset available. 

• Customer Retention Analysis: Analyze customer retention rates and identify key factors influencing customer loyalty by exploring transaction histories.
• Employee Attrition Prediction: Build a project analyzing employee data to find patterns and predict attrition. You might think about factors like job satisfaction and time with the company.
• E-commerce Inventory Optimization: Use historical sales data to help optimize stock levels for a business by forecasting demand.
• Social Media Sentiment Analysis: Perform sentiment analysis on social media posts or reviews to identify trends in public opinion for a specific brand or topic.
• Real Estate Market Analysis: Analyze real estate data to determine the best-performing neighborhoods based on property value trends and rental rates.
• Movie Rating Analysis: Explore data from a movie database to find trends in ratings and genres over time, identifying patterns in audience preferences.
• Retail Promotion Impact Analysis: Examine how specific promotions or discounts affect sales volume.
• Hospital Readmission Rates Analysis: Analyze healthcare data to identify trends in patient readmission rates.
• Public Transportation Usage Trends: Investigate patterns in public transportation usage to identify peak times and underutilized routes.
• Financial Fraud Detection: Develop a project that identifies potentially fraudulent financial transactions based on factors like transaction amount and frequency.

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 you're fully ready to start building these SQL projects and growing your professional portfolio. It's never too early or too lateto 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.