Machine learning and AI may dominate the tech headlines, but the most important skill in the data science industry is something much older — almost 50 years old, in fact! Despite its age, SQL is still the most important language for data work.

How has a five-decades-old language managed to remain so relevant in the ever-changing, fast-developing data science sector? We’ll get to that, but first, let’s answer a more fundamental question:

What is SQL?

SQL is what’s called a query language — a specific type of programming language that’s designed to facilitate interaction with databases. It was first developed in the 1970s for working with relational databases.

Although it’s been updated quite a bit over the years, that’s still what SQL is used for today: querying, updating, changing, adding, and deleting data in relational databases.

(By the way, SQL can be pronounced “sequel” or S.Q.L. — both pronunciations are widely used.)

In the context of data science work, SQL is often used in tandem with traditional programming languages like Python or R.

A data scientist might write a SQL query to pull specific data from a company database based on conditions outlined in the query. Then, they can use their Python or R skills to perform deeper analysis using the dataset their SQL query fetched.

Today, SQL is used as the basis of a wide variety of database management systems. The language itself is open-source, but companies like Microsoft have also developed “dialects” of SQL for use with their proprietary SQL database products, like Microsoft SQL Server.

Why do you need to learn SQL?

1. SQL databases are everywhere.

Just about every company on the planet stores data in some kind of database. And most of those databases are built using some kind of SQL-based technology.

According to Statista, the four most popular database management systems on earth are Oracle, MySQL, Microsoft SQL Server, and PostgreSQL. All four of these systems are SQL-based, and anyone working with them would benefit from having SQL skills.

In fact, of the top ten most popular database management systems, just two (MongDB and Redis) are not SQL-based.

But SQL is so popular that SQL skills are useful even for these database technologies, as solutions have been created to allow using SQL on both of these systems, too.

Long story short? Your company (or future company) has a database. If you want a job in data, you’re going to need to be able to query that database.

Statistically speaking, there’s a high probability that you’ll need SQL skills to do that — and even if your company is one of the relatively few that uses a non-SQL-based database management system, there’s a good chance your SQL skills will still be useful.

2. They’re moving onto the cloud, not going away.

SQL is definitely old, and it’s certainly not “sexy.” Bootcamps don’t run glossy ads promising to teach you SQL. But as previously mentioned, SQL-based databases are in use at almost every company on earth.

And far from going away, SQL is being implemented into the next generation of database technologies. With cloud databases in increasing demand, for example, cloud-based SQL database solutions like Microsoft’s Azure SQL Database, Google’s Cloud SQL, and more, are popping up left and right.

Relational databases may be an old technology, but that also means they’re proven. Most companies rely heavily on their SQL databases, and aren’t interested in fixing a system that isn’t broken. That means that SQL skills will be in demand for many years to come.

3. Employers demand you know SQL.

You don’t have to take my word on the first two reasons. If you doubt the importance of SQL skills, start looking at job postings for roles like “data analyst” or “data engineer” and see how many list SQL.

You’ll find that SQL skills are in demand for almost many jobs with “data” in the title. And for entry-level positions like data analyst, SQL comes up more frequently than any other technical skill (including Python, R, machine learning, and so on).

In fact, there are many data jobs where SQL skills (and some familiarity with spreadsheets) are the only technical skill required, or the only technical skill that’s tested as part of the interview process.

More advanced roles are also likely to require SQL. Data engineering jobs, for example, typically list SQL as a mandatory skill. As of this writing, more than 70% of the open “data engineer” jobs on list SQL.

How to Learn SQL

So SQL is a critical language to learn for working with data. How can you actually go about learning it?

There are many ways to learn SQL. And although marketers will sometimes tell you differently, no single approach is going to be right for everyone.

Some prefer free resources, like freeCodeCamp's SQL courses, others want to learn with interactive courses, and others prefer to learn via a university.

Before you choose a platform, you should consider factors including:

  • Your budget — Are you looking for something free? Are you willing to spend a little for the right learning platform? Are you looking for a university degree and are willing to spend a lot?
  • Your time — How much time do you have to learn? When will you be able to study? Different learning platforms and solutions have different time requirements, and some require a full-time commitment.
  • Your learning preferences — Do you learn best by doing? You may want to look for an interactive platform that lets you write and run SQL queries. Do you learn better from videos? You may want to look at video-lecture-based courses. Do you learn best with peers? You may want to look for a cohort-based in-person or online learning solution.

If you’re not sure what kind of platform or approach is best for you, you can always test out multiple options! Even the paid platforms typically have a free trial, some kind of free tier, or at least a sample lecture or two that you can peruse to see if the learning approach works for you.

Happy learning!