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Boost Data Potential wht SQL and Python

In this article, we will explain why using SQL with Python is an awesome combination for unleashing the full potential of your data! Read on to find out how learning and starting to use the most popular programming language can have a positive impact on your work.

You may be wondering why we write about Python on the blog? Well ... They are just a very good couple. Both languages are basic tools in such fields as data science and data visualization. They complement each other perfectly and strengthen their individual capabilities.

That's why I decided to show you how much you can gain by learning the basics of Python. I know that many people reading this article are still on the path of learning SQL and do not currently have the space to learn another skill. It’s usually best to master oneskill – in this case, SQL – and then move on to the next challenge.

However, it is worth planning your development path in advance. That's why I decided to describe how using SQL with Python will help you spread your wings and boost your career.

If you are just starting out with SQL and learning Python seems very far away, I recommend our SQL Basics course. It's the perfect step into the world of relational databases. You'll get a solid foundation in SQL.

The Importance of Data

Nowadays, data has become an essential resource for almost all companies, no matter their size and field of expertise. Data helps companies to understand their customers better, providing high-value insights.

By collecting and analyzing data, companies can define a target audience and get feedback for each product. They can then make informed decisions on improving their product, marketing it, launching a new product, and even canceling an underperforming product. This leads to better customer satisfaction and loyalty.

In a more general way, data can help companies to identify opportunities for growth. It can help optimize processes and improve efficiency by identifying bottlenecks, inefficiencies, and opportunities for automation. Data can make it easier to take high-level decisions in a fast-changing business environment (we could figure it out during the pandemic!) and develop strategies to stay ahead of the competition.

Enhancing SQL with Python

Data has also become a strategic asset in terms of financial valuation. When an organization wants to raise funds, start an initial public offering (IPO), or even make a sale offer, it has to be valued first . Data has become a key element for financial valuations, especially for tech companies. If you want to know more about it, you should read this excellent paper by Deloitte.

You may have heard the term “data-driven”. It’s used to describe the preference for using data for decision-making and problem-solving instead of relying on subjective sources such as opinions or intuitions. Forget about “having a great idea” or “experimenting” blindly with something new; every decision should be supported by data. Data-driven strategies reduce conjectures and lead to better results.

Why Is SQL Worth Knowing?

You may think: “Hey, why is this guy suddenly switching to SQL? What does it have to do with the previous section?” Simple. If you have carefully read the previous section (I hope so!), you’ve probably been convinced of the importance of collecting and using data.

There are many ways to store data, but it’s highly probable that the data will be stored in a database. And what is the leading language to manage databases? SQL! So if you want to work with data (collect it, analyze it, process it, etc.), you should have a solid knowledge of SQL.

SQL (Structured Query Language) is the industry standard language for communicating with relational databases. (Non-relational databases exist, but they’re outside the scope of this article.) It allows retrieving and storing data in a database, updating existing data, and deleting data.

SQL is over 50 years old and still very popular. According to the Stack Overflow Developer Survey 2022, SQL dialects (aka small variations of standard SQL) are the most popular programming languages for database developers. But why is it so popular?

First of all, SQL is a standardized language. This means that you can use SQL to work with data, no matter which database technology you use. Even SQL dialects are mutually intelligible and don’t represent a difficulty. It’s like when you move from one US state to another; people may have different accents, but you can still understand them. You can read more about SQL dialects in this article.

SQL is also a very flexible and easy-to-understand language. You can achieve complex queries to manipulate massive data in a few lines. Let’s check the following code:

FROM Users 
WHERE job=’engineer’ AND country=’France’

In the above example, we have retrieved records for all the engineers living in France. Simple, isn’t it? The syntax is very understandable – even to non-developers.’s Interactive Courses

At this point, I hope that I piqued your curiosity and you want to learn SQL. There are multiple ways to do this. You could, for example, watch videos on YouTube. But let’s be honest: watching a guy for hours instead of writing your own code can be discouraging. (It personally upsets me; don’t judge!) And if you decide to try to code along, you will lose time by playing back concepts you’ve missed and switching between the video and your SQL editor.

The best way to learn SQL is undoubtedly through interactive courses like those on! Look at the following screenshot:

Enhancing SQL with Python

An interactive SQL course on

The lesson is on the left part of the screen, and you have a SQL editor in the right part of the screen to execute ALL the queries you want to try without restrictions. You will be asked to solve a small exercise related to the lesson to check your SQL knowledge; the platform will indicate if you are right and give you some hints if you need them. The best part is that you don’t need to install anything on your computer. You only need a web browser (and an Internet connection, of course!).

What Is Python?

Python is a powerful programming language that can be used to build almost anything: web applications, games, chatbots, machine learning models, scripts, and more.

Although Python became trendy a few years ago, it is over 30 years old! This veteran language was released at the beginning of the 90s as a scripting language. Its massive popularity came along with the rise of AI and machine learning.

According to the Stack Overflow Developer Survey 2022, Python is one of the most popular programming languages for developers. Why?

Enhancing SQL with Python

First of all, Python is well-known for its simplicity and readability. It’s a perfect fit for beginning developers. Its syntax is clear and does not contain lots of confusing brackets or curly braces. Look at the following piece of Python code:

import random

def get_random_number():
return random.randint(50, 100)

print("Here is a random number: ", get_random_number())

The above Python code generates a random number between 50 and 100 and displays it on the screen. Simple, right? The code is very understandable because the indentation is mandatory, which reduces messy code.

Furthermore, Python has an awesome and supportive community that develops new features and modules; you can check their fantastic work on PyPi, the official Python repository.

And talking of the community, don’t worry if you struggle with your code! There will always be an anonymous hero to help you on a collaborative website like Stack Overflow. Look at that: more than 2 million questions related to Python; that’s humongous!

Python: The Basic Language of Data Science

Over the last decade, Python has established itself as the basic language of data science. Data science can be described as the discipline of using scientific methods to collect, analyze, and gather insights from data. Python provides plenty of great frameworks and libraries to work with large sets of data.

You may have heard about NumPy or pandas; both allow manipulating and analyzing data. Then you can show the data you have previously analyzed and visualize patterns and relations in it, thanks to libraries like Matplotlib and seaborn. You can build complex machine learning data models with libraries like scikit-learn or TensorFlow.

It’s all about data! That is why “Python and SQL are a match made in heaven”, as Rebecca McKeown said in her excellent article Top 5 Programming Languages to Learn Alongside SQL. Although Python and SQL are different programming languages and are used in different scenarios, they can be a good combination for powerful data-driven applications.

A data-driven application using SQL and Python could be summarized this way:

Enhancing SQL with Python’s Interactive Courses

Did you like what I showed you about If you did, you’ll probably also love! Have a look:

Enhancing SQL with Python

An interactive Python course on

Same awesome interface, same simplicity!

I will give you some great info: At the time of writing this article, the interactive Python Basics: Part 1 course is totally free! Just create a free account and start learning. And if you like it, you can continue with the Python for Data Science mini-track. It’s a perfect fit for beginner data scientists who want to learn data science and Python.

If you are motivated to start a Python career, I recommend you read my article on the Python Developer Career Path.

Using SQL with Python Is Awesome!

I truly hope this article motivated you to learn both SQL and Python! You can find all the courses you  need to get started on and Soon, you’ll be able to work with data and create awesome data-driven applications.

So, what are you waiting for? Learn SQL and Python and become a data expert!