Do you speak data? Write your SQL request — the universal language of data

Everyone knows how to search on Google. Google handles approximately 16.4 billion searches every day.

The idea behind SQL is the same, except instead of searching for webpages, you search for your own data. Contrary to popular belief, SQL is not just for developers. With practice, you can easily master the language and become fluent.

In this module, you will learn how to edit your first SQL request, which will help you to understand other commands once you have grasped the key concepts of SQL syntax.

What is SQL?

SQL (Structured Query Language) is the universal language for querying databases. Imagine a database as a set of organised tables: one listing your customers, another listing their orders and another listing their account details. SQL enables you to ask questions across all of these tables.

For example, which customers placed more than three orders last month? Which regions generated the most revenue? SQL provides the answers to these questions.

SQL has been around since the 1970s, developed by IBM researchers who needed a simple way to retrieve data from relational databases. It was standardised in 1986 and has barely changed since. Decades later, it remains the most widely used data language in the world.

What Can you Do with SQL?

The language essentially consists of four fundamental actions: reading, filtering, sorting and counting. For this module, we will use a customer database with the following fields: first name, last name, city of birth.

To improve understanding, I have created a table named pm_table showing all the people who have served as Queen Elizabeth II’s Prime Minister.

Using this dataset, we can query any information we want in SQL, such as a list of all prime ministers born after 1945. You can also request a list of people whose names contain the letter 'a'.

For more complex datasets, you have the ability to create new columns from calculated measures derived from existing ones. For instance, if your table contains a unit price column and a quantity column, SQL can automatically generate a total revenue column by multiplying the two — without altering the original data.

Your First SQL Query

Every SQL query follows the same three-part structure — and once you've seen it once, you'll recognise it everywhere.

• SELECT tells the database what you want to see. Which columns? Which information?
• FROM tells the database where to look
• WHERE tells the database which rows to return. What condition must be met ?

Let's build on our previous example. This time, we want to extract the list of prime ministers born after 1945 — which means adding a condition based on a numerical value.

Notice the > operator in the WHERE clause. SQL supports a full set of logical operators — >, <, =, >=, <=. It’s allowing you to filter data with precision. The logic is the same as in everyday language: "greater than", "less than", "equal to".

Why SQL is crucial in 2026?

Even without writing SQL queries, understand its logic help you to better frame needs to your data team. It enhances as well, your comprehension when reading a data report and ask the right questions.

In a world where tools evolve faster than most people can keep up, SQL is a rare exception. Since its standardisation in 1986, its core syntax has barely changed — the query you write today looks almost identical to one written forty years ago. No steep learning curve, no constant retraining. Just one language, universally understood across industries, tools, and teams.