June 12, 2024

How to Learn SQL: The Best Way

Condensing and organizing data

As I transitioned from high school teacher to data analytics professional, I quickly realized how important SQL skills are. Nearly every data job listing I saw highlighted SQL as a must-have.

At first, learning SQL felt overwhelming. Complex concepts like CTEs and window functions seemed out of reach. The various SQL dialects used for different roles added to the challenge. But as I progressed and began incorporating SQL into my job, the benefits became clear:

  • I could automate data tasks and work far more efficiently
  • My SQL expertise made me a go-to resource on my team
  • Across industries, SQL opened doors to exciting data career paths

In this guide, we'll explore why learning SQL is so important and share strategies on how to learn SQL. By approaching SQL the right way, you can gain a valuable skill set for making data-driven decisions in any field. Let's jump in!

Why learn SQL?

If you want to boost your data career, learning SQL is an excellent place to start. This powerful programming language is essential for managing and analyzing data, and it's in high demand across industries.

Consider this:

  • Almost every company uses some kind of SQL-based database to store data. MySQL, Oracle, Microsoft SQL Server, etc. — all of these are SQL-based database management systems, and that means that SQL skills will be needed to work efficiently with databases at almost any company.
  • SQL enables you to work more efficiently and transparently than Excel. SQL enables you to work with huge datasets quickly. And because it’s a written language, everything that you do is transparent and easy to understand, adapt, and repeat. No hidden cell formulas to go looking for, and no more complicated VLOOKUP nightmares!
  • SQL skills are in demand. In fact, SQL is one of the most desired programming languages among developers.*
    And to top it off, employeers commonly list SQL as a required skill in data-related job posts.*

So what makes SQL so valuable? For starters, it allows you to efficiently manage and analyze large datasets and is used in nearly every industry.

Not only does SQL open up job opportunities, it can also lead to career advancement and higher earning potential. If you're looking to gain this in-demand skill, Dataquest's SQL Fundamentals path is a comprehensive way forward. You'll be querying databases with confidence in no time!

Why most new learners fail

Learning SQL can be tough, and many beginners give up when they hit a roadblock. Why is that?

The most common reasons new SQL learners fail include:

  • Difficulty understanding ideas like joins and subqueries
  • Not enough hands-on practice, leading to forgetting keywords or the SQL order of operations
  • Information overload and ineffective teaching methods

The problem with most learning resources

Learning SQL is an important skill, but unfortunately, many SQL courses fall short in preparing you to use databases in the real world. Have you ever taken an SQL course only to struggle to apply what you learned to actual data or projects?

The issue is that a lot of SQL learning resources focus on syntax without connecting the concepts to practical examples. They may teach you the fundamentals, but they don't show you how to solve real problems or work with authentic databases.

Some of the main problems with typical SQL learning resources include:

  • Using simplified, unrealistic example datasets that don't reflect real-world data challenges
  • Neglecting important topics like database design principles and complex querying scenarios
  • Not providing sufficient opportunity to practice applying SQL skills to actual business problems

For instance, one common issue is that SQL courses use simplified datasets that don't reflect the complexity of real-world databases. While these examples can help you practice writing queries, they don't prepare you for working with actual data, which may have quality issues, confusing naming conventions, or inefficient designs. In fact, flawed databases and poorly written queries are a frequent cause of data issues in many companies*.

Another problem is that many SQL tutorials don't cover critical topics like database design principles or advanced querying scenarios. Without exposure to these concepts, aspiring SQL users can inadvertently develop bad habits that hinder their effectiveness*.

The most effective SQL learning resources are those that integrate real-world datasets, scenarios, and best practices from the beginning. They challenge you to apply your skills to solve problems so that you're prepared to work with SQL in a professional setting.

How to Learn SQL (The Best Way!)

Graphic shows the importance of building data projects

Learning SQL doesn't have to be a struggle. While many beginners get tripped up by abstract concepts and lack of hands-on practice, there's a better way. The key? Diving into SQL projects you genuinely care about.

When I was learning SQL myself, I found the most success by working on projects related to my interests. Not only did this help me grasp SQL's real-world applications, but it also allowed me to build up a portfolio and maintain motivation. Getting my hands dirty with actual data, constructing databases, and tackling authentic problems made the whole process concrete and gratifying.

So how can you put this project-centric approach into action? The following five steps will help guide you to a great, personalized SQL learning experience:

Getting started with SQL

Like any new skill, it can feel overwhelming to know how to start. Let's go step by step in breaking down the most valuable parts of learning SQL:

Step 1: identifying motivation

Before diving headfirst into learning SQL, it's important to understand your motivation. Why do you want to learn this skill? Identifying your purpose will help you stay focused and driven, even when the concepts get challenging.

People are drawn to SQL for different reasons. Maybe you're excited by the prospect of using SQL to conduct advanced data analysis and make data-driven decisions. Or perhaps you're motivated by the abundance of career opportunities in fields like data analysis, business intelligence, and data science.

For example, let's say you're a marketing professional who wants to transition into a data analyst role. In this case, your motivation might be to gain the SQL skills to analyze customer data, identify trends, and inform marketing strategies. This clear purpose can help you power through the learning process.

What to ask yourself

To pinpoint your own motivations, think about how SQL aligns with your current job or desired career path. Ask yourself:

  • What specific outcomes do I hope to achieve by learning SQL?
  • Which aspects of working with SQL excite me the most?

Reflecting on these questions can clarify your goals and strengthen your commitment to learning. It's helpful to focus on one or two key motivations to maintain a targeted approach. You might find it beneficial to journal about your learning journey or discuss your goals with a mentor.

Setting achievable goals for both the short-term and long-term can also sustain your motivation. Make sure these goals are specific, measurable, achievable, relevant, and time-bound (SMART).

In summary, understanding your personal motivation is essential for successfully learning SQL and reaching your broader career objectives. By identifying what drives you, you'll find the learning process more engaging and purposeful.

Step 2: learning the basics quickly

So now you've identified your motivation and you want to start using SQ,L but you're not sure where to begin? The key is to focus on the fundamentals and use interactive learning tools. This way, you can grasp the essentials without getting overwhelmed.

So what are the basic SQL skills for beginners? Let's break it down:

  • SELECT statements: The foundation for fetching data from a database.
  • JOINs: How you combine rows from multiple tables based on a shared column.
  • Subqueries: Handy for conducting complex queries within other SQL statements.

The best way to learn is by doing. Look for hands-on courses that start simple and gradually introduce more advanced concepts. Engaging with real datasets through interactive lessons, like those in Dataquest's SQL Fundamentals path, helps cement your understanding.

Here are some top resources we recommend for getting started with SQL:

By focusing on core skills through engaging, interactive platforms, SQL beginners can build a strong foundation quickly and stay motivated to keep learning.

Step 3: work on guided projects

Want to refine and, more importantly, remember the SQL skills you just learned? Completing structured, guided projects is key. This allows you to apply what you've learned, reinforce concepts, and build confidence until you feel comfortable enough to work on independent projects.

Here are some examples of some of Dataquest's SQL guided projects:

  • Analyzing Kickstarter Projects: Assume the role of a data analyst at a startup considering launching a Kickstarter campaign. Using SQL, you'll analyze a database of Kickstarter projects to uncover insights so your team understands what influences a campaign's success. This hands-on project allows you to apply SQL skills like querying, filtering, sorting, and conditional logic with real-world crowdfunding data.
  • Customer and Products Analysis: Act as a data analyst at a scale model car company. Use SQL skills like joins, subqueries and CTEs in the company's sales database and answer to business questions about inventory, customers, and marketing.
  • Window Functions for Northwind Trading Company: Step into the role of a data analyst at Northwind Traders, a global gourmet food distributor. Using advanced SQL techniques like window functions and common table expressions (CTEs) on the company's database, you'll analyze sales data to provide actionable insights that drive strategic business decisions.
  • Analyzing CIA Factbook Data: Step into the role of a data analyst exploring the CIA World Factbook, a compendium of country statistics. Using SQL queries in Jupyter Notebook, you'll analyze demographic data like population, population growth, birth rates, and death rates to uncover insights about countries worldwide.
  • Building a Database for Crime Reports: Act as a database administrator tasked with building a PostgreSQL database to store and manage data on actual crime reports in Boston. By applying your skills in database design, table creation, data loading, and user management, you'll develop an organized system for this important real-world dataset.
  • Designing and Creating a Database: Act as a a data engineer tasked with converting historical Major League Baseball game statistics from a large CSV file into a robust, normalized SQL database optimized for analysis. You'll design a database schema, create tables using SQL, and migrate data from CSV files.

Finding Project Inspiration

Remember, there is no single "right place" to start when it comes to structured projects. Let your motivations and goals guide you.

Are you interested in data analytics or data science? Do you want to build a database, or just query an existing one? Here are some recommended resources for inspiration:

Data Engineering

  • Library Management System using MySQL: Create a Library Management System using SQL to manage a library's book inventory, track borrowed books, and maintain user records. You'll design and implement a relational database from scratch, creating tables to store book and user data, and writing queries to perform common library tasks.
  • E-commerce Order Management System with SQL: Develop a database for an online retail store, giving you hands-on experience with using SQL to manage and analyze e-commerce data. You'll design and create tables for products, customers, orders, and reviews, and write SQL queries to process orders, update inventory, and generate sales reports.
  • How to Design Database for Flight Reservation System: Create a database for an airlines reservation system using SQL. The database will manage flight schedules, passenger information, and bookings. You'll design tables to store data on flights, passengers, and reservations, and write SQL queries to manage and retrieve this data efficiently.

Data Analytics and Data Science

  • Superstore Sales Analysis: Work with the superstore dataset to answer business questions.
  • Fraud Detection with SQL: Work with multiple CSV files to create a database schema and database, then query your new database to identify potentially fraudulent transactions.

The bottom line? Structured SQL projects are an effective way to deepen your understanding, gain practical experience, and demonstrate your abilities to tackle real data scenarios. So explore the resources available and start building your SQL project portfolio today!

Step 4: build your own SQL projects

You've built a solid foundation in SQL through structured projects - now it's time to advance your skills with independent work.

Tackling real-world datasets on your own is the next step to mastering SQL and preparing for data roles. But where do you begin?

Start small, focusing on topics that fascinate you or align with your career goals. As you gain confidence, you can gradually take on more complex analyses.

Here are five tips for finding engaging SQL project ideas:

  1. Expand previous projects by adding new features or insights
  2. Explore curated lists like Dataquest's "10 Exciting SQL Project Ideas for Beginners"
  3. Join online SQL challenges to solve real-time problems
  4. Analyze industry-specific data for targeted insights
  5. Build useful tools with SQL databases

Independent projects aren't always smooth sailing, but challenges are opportunities to grow. Try these strategies to stay motivated:

  • Adopt a growth mindset - setbacks are chances to learn
  • Break big tasks into manageable steps with realistic goals
  • Lean on the SQL community when stuck - forums like Stack Overflow are invaluable

If you hit a wall, these top resources can help you troubleshoot:

Independent SQL projects sharpen both your technical abilities and problem-solving skills, setting you up for success in advanced data analytics roles.

Embrace the challenges as opportunities to learn, and make the most of the wealth of SQL resources available online. With dedication and persistence, you'll be amazed at how far your SQL skills can take you!

Step 5: work on more advanced projects

Consistently challenging yourself with complex SQL projects is the best way to remember advanced concepts and prepare for real-world data analysis.

What does this look like in practice? Engaging in projects that involve joins, subqueries, and combining data from multiple sources will stretch your capabilities. Peer-to-peer learning, focusing on analytical thinking, and practicing writing efficient queries on large datasets are all effective ways to level up.

Ready for some project ideas to put your skills to the test? Here are five advanced SQL challenges to tackle:

  • Build a comprehensive railway management system
  • Create a robust data warehousing system
  • Analyze data from a digital music store
  • Develop an inventory control management database
  • Analyze motorcycle part sales or a similar niche market

Regularly challenging yourself with these kinds of projects will deepen your understanding of advanced SQL, keep you moving forward, and set you up for success in data-focused roles.


Learning SQL is a journey with real-world impact. The skills you gain, from basic queries to advanced functions, will serve you well in your data career.

To keep growing, seek out SQL projects, engage with data communities, and contribute to open-source work. Interactive courses like Dataquest's SQL Fundamentals provide hands-on practice to reinforce your skills.

With dedication to continuous learning and real-world application of your skills, the benefits to your data career will be significant. Keep exploring, practicing, and using SQL to solve data challenges. You've got this!

Frequently-asked questions about SQL:

Is SQL difficult to learn?

That's a very personal question — what's very easy to one person may seem very difficult to the next, and vice versa. However, most people find SQL pretty easy to learn, especially when compared to full-on programming languages like Python or R.

That's because unlike a “full” programming language, SQL is a query language. It's built specifically for interacting with relational database management systems such as Microsoft SQL Server, Oracle, SQLite, MySQL, etc. For that reason, there's not as much to learn, and some of the more complex concepts that exist by necessity in more holistic programming languages aren't a factor in SQL.

That said, the fact that most people find SQL relatively easy to learn does not mean that you will, or that you should feel ashamed if you find it challenging! Particularly if this is your first foray into the world of programming, you should be ready for a challenge.

(But don't worry. No matter what your background is, you can totally learn SQL. Our community is here to help you anytime you need it!)

SQL or Python: which is better to learn?

The answer to this question really depends on your goals. They're very different things.

SQL is a query language. It's really only useful for interacting with, filtering, and lightly analyzing data from databases. It offers a lot of power for working with data in those contexts, but it can't do all the things a full programming language like Python can do.

Python is a programming language. That makes it a bit more complex to learn, but it also means it can do a lot more. You can analyze data in Python, but you can also use it to build machine learning models, make video games, program a robot, or design art.

If you work with data often — if you're opening spreadsheets every day and you know what VLOOKUP is — there's a good chance you'd benefit from learning both languages.

At Dataquest, we teach both Python and SQL as part of our Data Analyst and Data Scientist career paths. Both skills are required for full-time data jobs (although R can be substituted for Python, learning SQL is non-negotiable).

Can you learn SQL on your own?

Yes. We've seen thousands of students do exactly that, working through our interactive SQL courses on their own time, at their own pace.

Even if you're not using Dataquest, it is absolutely possible to learn SQL on your own. Having a supportive community you can turn to for help certainly can make things easier, though!

How long does it take to learn SQL?

The answer to this question depends on both your background and your goals for learning SQL.

So, rather than giving you a one-size-fits-all answer, let’s break this down into a few different scenarios. Each scenario assumes you're starting from scratch with SQL, and are looking to learn up through and including the specified skill level.

Feel free to jump to whichever of these subheadings describes you best:

(Note: all of the time estimates here assume you already have a full-time job and, like most adults, are limited to just a few hours a week of study time. If you can devote more time each week to studying, you’ll progress even faster).

No programming experience, and want to learn through basic SQL

Maybe your job isn’t technical, but you’re interested in learning a bit more from your company’s data, or running a few specific queries regularly to understand more about the impact of the work you’re doing. If you’ve never written code before, but you’d like to learn enough SQL to run a quick query to answer questions every now and then, this section is for you.

The fundamentals of SQL really won’t take very long to learn. Our first SQL course, for example, takes most people about an hour to complete.

Because you don’t have prior experience with programming languages, you’ll probably want to set aside a little extra time to wrap your head around everything. And you’ll definitely want to set aside some extra time for practice.

Even so, you should expect to be able to learn the fundamentals of SQL — how to query specific data tables from your database, how to select specific columns from those tables, how to do basic math with SQL, and how to limit the output your queries return — in the space of a few hours, or a weekend at most.

No programming experience, and want to learn through intermediate SQL

If you don’t have prior coding experience, but you’re expecting to use SQL pretty regularly, and take on some more complicated tasks like joining different tables together to create new tables for analysis, this section describes you.

How much time this takes will vary a bit from person to person, but you should expect it to take anywhere from a single weekend to a few weeks (we’re assuming that you have a full-time job already and are only able to study occasionally, during your free time).

If you’re studying with Dataquest, this section would map onto our first two or three SQL courses, depending on how much you need to learn for your specific use case. You can probably complete all three courses in around five or six hours, but you should definitely set aside extra time for practice and to work through the projects to cement your learning.

No programming experience, and want to learn through advanced SQL

If you don’t have coding experience but you’re looking to land a role that’s heavily reliant on SQL skills, like a data analyst job or perhaps even a data engineering job, this section is for you.

You’ll want to learn everything from the basics through advanced queries, but you’ll probably also want to learn skills like creating databases using PostgreSQL.

Depending on how deep you need to go, this is likely to take anywhere from a month to several months, because you’ll be learning advanced queries, but you’ll also need to cover topics like building and optimizing databases, database security, etc.

Note that if you’re looking for a job like data engineer, SQL skills are not the only thing you’ll need to learn, so the amount of time it takes you to get to job-ready will be quite a bit longer than the time it takes to learn SQL. Some data analyst jobs will also have additional technical requirements, like some knowledge of Python programming, although there are analyst jobs that only require SQL.

Prior programming experience, and want to learn through basic SQL

If you’ve already got some experience with programming languages and you just want to learn enough to query your company’s database for the right tables — maybe you’re planning to pull that data into Python or R for analysis — this section is for you.

The basics of SQL likely will take you just an hour or two to learn. You’ll probably find it to be refreshingly straightforward compared to other programming languages, as SQL is quite readable.

Prior programming experience, and want to learn through intermediate SQL

If you’ve already got some coding experience, but you anticipate using SQL fairly regularly to do things like join data tables on different columns and filter for the specific data you need, this section is for you.

Precisely how long it takes will depend on how far you want to go with SQL, but you will probably be able to comfortably work through the material our first two or three SQL courses in a week. Completing the guided projects may extend that time a little further, but you’ll probably be able to start querying your company’s database and using your new SQL skills in meaningful ways within just a few hours of beginning your study.

Prior programming experience, and want to learn through advanced SQL

If you’ve already got some coding experience but you’re looking to move into a full-time role that’s going to require a lot of SQL work, this section is for you.

You’ll want to learn all of the querying skills from the previous section, but you may also need to learn more about creating databases, optimizing them, and ensuring that they are secure. This means you’ll need to spend additional time learning about things like PostgreSQL, and think about the SQL skills you need from a data engineer’s perspective.

This will probably take you a month or two, although it’s worth noting that these kinds of roles will generally also require other technical skills that’ll take additional time to learn if you don’t already know them.

What are some good SQL resources to use?

  • Learning SQL 2nd Edition (PDF) — This O’Reilly book on the basics of SQL is available for free in PDF format, and makes a good reference.
  • StackOverflow SQL questions — Chances are, any SQL question you’ll have has already been answered here. But if it hasn’t create an account and ask it for yourself!
  • Github — If SQL is your first foray into the world of programming, you may not have an account here. If that’s the case, set one up and start learning how to use it! Github is great for sharing your own SQL projects with the world (and potential employers), and it’s also an amazing resource for looking at other people’s code.
  • /r/SQL — Reddit has a SQL community that’s large, active, and (mostly) happy to answer questions.
  • The Dataquest community — Our community is active, friendly, and ready to help you with all your SQL questions. Best of all, it’s open to everyone — you don’t have to be a Dataquest subscriber to get help there.
Anna Strahl

About the author

Anna Strahl

A former math teacher of 8 years, Anna always had a passion for learning and exploring new things. On weekends, you'll often find her performing improv or playing chess.