Hey you all!
It’s Josep here again! Sorry for the time out, a lot has been changing in my life lately.
The first big change?
I've quit my full-time job to become a freelancer!
(At least for now…! 🤐)
It's both scary and exciting, and I'll share more about it in the upcoming issues. There's been a lot of work and planning to do. Now that I have more time to create content, I'll be rethinking my whole strategy to be more personal and less robotic here.
This means… a lot of surprises are on their way! 😉
But today I want to write a bit about a question I have been receiving a lot lately…
What tool should I learn to crush into the data world?
Many of you have been asking how to get started in the data world. I know it can seem complex and intimidating, but fear often clouds our vision.
That's why I want to remind you all that SQL is still the number one data language and the easiest one to learn.
If you're looking to break into this field, there’s not better advice than…
START
LEARNING
RIGHT
NOW!!
Still not sure? Let’s give some reasons why 👇🏻
Humankind has always been strongly shaped by its ability to store and share information. Studies indicate that a key distinction between humans and other animals lies in our ability to create, preserve, and inherit knowledge and culture across generations.
And guess what… all of this is just DATA!
Today we are amid a significant shift in how our world works: Data has become the fuel of the XXI century. All fields and sectors rely on it to make decisions.
One thing is certain: The need for data-related skills will only keep surging.
Organisations today gather raw data from both internal and external sources at an unprecedented rate. By analysing this data, they can use reporting applications, dashboards, and other tools to answer questions and gain valuable insights.
So the right question to be done is how to manage all this data?
And the answer is quite simple: SQL remains the best option to do so.
You can go check the latest StackOverflow Developer Survey 2023, where SQL stands as the 3rd most used programming language of all developers!
(And the first one if we only consider those used in the data science field 🥇)
So let’s try to understand better SQL’s advantages 💥
SQL’s main advantages
#1. It can deal with big amounts of Data
SQL is designed to work with big data and can handle complex queries on large datasets much faster than other tools like spreadsheets or even some programming languages like Python.
Learning SQL helps you manage and analyze big data effectively.
In many organizations, the core of the data environment is typically a data warehouse, where SQL is the primary language for interaction.
#2. It can be easily integrated with other tools
SQL integrates seamlessly with other data science tools and programming languages, such as Python and R. Libraries like pandas (Python) and dplyr (R) allow you to run SQL queries directly within your code.
This interoperability makes it easier to combine SQL's data handling capabilities with the advanced analytics, visualization and ML features of these languages.
#3. It is standardized
To query or manipulate data with SQL, you use statements with keywords such as SELECT
and FROM
. This SQL syntax is standardized by ANSI and ISO-certified, ensuring consistency across the hundreds of databases and data tools that support SQL today.
While some databases and tools may extend the syntax with specialized operators, commands, or functions, the fundamental principles of SQL remain consistent.
Once you master the basics of SQL, you can apply this knowledge universally across different platforms.
#4. It is easy to understand
Basic SQL syntax is highly readable, resembling natural language. It outlines how data should be retrieved or manipulated.
Consider the following example query:
SELECT
first_name,
last_name,
date_of_hire
FROM employees
WHERE date_of_hire > '2018-12-31'
ORDER BY date_of_hire, last_name
In this query, the SQL keywords SELECT
, FROM
, WHERE
, and ORDER BY
define the actions to be performed and any person can understand the main purpose of the query.
⚠️ It is important to consider that while these keywords don't need to be capitalized, it's a common convention to do so for better readability.
And finally…
How to get started with SQL?
Here's a step-by-step guide to get you started:
Basic SQL Statements: Start with the basic SQL statements to retrieve data and manipulate tables.
Aggregate Functions: Learn aggregate functions like SUM and AVG to summarise data and perform initial analyses on a single table.
JOINs and Subqueries: Move on to using JOINs and subqueries to combine data from multiple tables.
Once you know the basics, it is important to start doing your hands-on projects.
If you have doubts about how to start, you can easily answer this mail or contact me via any of my social networks and I’ll be more than happy to help you all guys!
Are you still here? 🧐
👉🏻 This is a transition post for my upcoming issues, so…
Please, let me know any feedback for the upcoming issues.
If you like this new personal approach, please pass by and drop a Hi! in the comments! 👋🏻
My latest articles 📝
Exploring Google’s Latest AI Tools: A Beginner’s Guide in KDnuggets.
The Best Strategies for Fine-Tuning Large Language Models in KDnuggets.
A Comprehensive Guide to Working with Mistral Large in DataCamp.
Want to get more of my content? 🙋🏻♂️
Reach me on:
LinkedIn, X (Twitter), or Threads to get daily posts about Data Science.
My Medium Blog to learn more about Data Science, Machine Learning, and AI.
Just email me at rfeers@gmail.com for any inquiries or to ask for help! 🤓
Nice article, thanks for sharing this awesome information. Your article is more helpful for anyone who interested to kick start his career or journey to data.
I’m asking for a roadmap to learn and improve SQL skills?