6 Reasons To Learn About Data Analytics

Analytic Graph Ironhack

You’re probably heard the word “Big Data” over a million times! This has become a huge buzzword yet few people really knew what it meant. A couple of years have passed and data has become a key stake for all companies, whether they are in tech or not. The digitalization of clients’ information and products have generated a huge amount of data that companies can now use to make business decisions. 

For a career in Data Analytics, most cases you will need to attend school. While age is not an issue to start learning about data, it does require time and consistent effort. Whether you decide to take a bootcamp or college, here are 6 reasons to learn about Data.

1. Companies are using your personal data!

Every week (day?) reveals a new scandal about the misappropriation or misuse of personal data. Whether it’s by private companies or governments GDPR (RGDP in French) has been a key evolution of the laws governing the use of data.

Learning how to manipulate data sets contributes to your understanding of your own data, how it is used and whether or not you should let others use it. Do you want to know how Google and Facebook are using your personal data? Or who you can trust vs. who you can’t? By educating yourself on data analytics you'll understand a website’s terms and conditions and read through its code to understand how it all works behind the scenes.

2. Data is highly valued in companies

Data professionals are of huge importance in all companies. They hold the skills that will allow them to gather and analyze data so it can serve as crucial information in all decision making processes. What are the most popular products we sell? What products should we upsell when someone buys something from our website? What services should we add to our current business model? Are our employees happy? Are we following diversity laws in our company? These are all questions data professionals can help answer.

3. There are thousands of open positions for data professionals

Forbes Magazine has ranked Artificial Intelligence (A.I.) and Data Science respectively as #1 and #3 of the most wanted tech skills for 2018. That’s not even mentioning the fact that Analytics positions are also in very high demand and featured in that ranking. If you take a look at Linkedin, you’ll see over 21,000 data job openings in the United States. Welcome To The Jungle (the leading website for startup jobs in France), you’ll see around 3000 open positions for data professionals. This allows for good salary and benefits. The average salary for a Data Analyst is between 40K€ and 50K€ according to Glassdoor. Not bad!

Are you enjoying this article? Keep learning about Data Analytics!

Take the first step into tech and find out more about our Data Analytics bootcamp

4. Upskill Your Tech Career 

It’s totally understandable that you don’t want to switch your tech job for a career in data. But no matter what position you hold, it’s also very likely that knowing how to manipulate and visualize data will help you in your current job. Marketers, Product Owners, Growth Hackers, Business Development...These are all fields where knowing data analytics will become a solid asset to provide value to the company. As we said earlier, all key decisions go through data analytics nowadays.

If you decide to transition as a data analyst, get ready to make key business decisions for your department. Your work will be analyzed by leaders and industry experts. Grow into your career as a Data scientist or Data engineer. 

Maybe you don’t want a career in Data. That’s totally fine. This is a great way to empower your existing career and become a liaison to the data team.

5. You’ll actually learn to code

Think Data Analytics is about knowing a few Excel formulas? Think again. Excel is a great tool, but a true master of data knows how to code in a programming language called Python. The syntax of Python is quite easy to understand, and yet Python is powerful enough to be able to gather, organize and interpret data sets with great precision.

Learning a programming language is a fantastic experience by itself, doing it so that it becomes useful in your job and career is simply awesome. Oh and once you learn how to code in one language, the next ones are a lot easier to learn.

6. Data is not just for logical geeks, it’s also for the creative minds

When we talk about MySQL, Machine Learning, A.I. or coding in general, creativity may seem like a far away thing that has nothing to do with this geeky stuff. And yet, creativity is essential in those fields. A huge part of Data Analytics is also about having creative ideas about how to answer a difficult question or provide solutions to a complex problem. Another key stake for companies is making data accessible to the many so all employees can benefit from it. Here enters Data Visualization, which is about how you can creatively take sets of data and turn them into graphics and infographics people can actually understand. A few examples of this are “a day in the life of Americans”, “the daily routine of the most creative minds or “from the nanoscale to the universe”.

Are you interested in data and how learning about it can either help you switch careers or improve in your current field? Check out our Data Analytics Bootcamp program which will help you become a true data expert.

Join Ironhack

Ready to join?

+10,000 career changers and entrepreneurs launched their careers in the tech industry with Ironhack's bootcamps. Take a step forward and join the tech revolution!


What would you like to learn?


Where would you like to study?

Related blog posts about Data Analytics

Data Analytics Is Changing The World - Here’s Why You Should Care


Data Analytics Basics: Learn From Anywhere!


Telling Compelling Stories With Data


How Much You Can Earn in London As a Data Analyst


How to Improve Your Python Skills


The 5 Most In-Demand Machine Learning Languages in 2022

Ironhack Data Analytics

How to get into data science

image with code for data and tech

Differences between data analytics and data mining


Best Way To Start Learning Data Analytics

business analytics

What is the difference between business intelligence and business analytics?

image of a tech girl working on her macbook and a colleague sit behind her

How Do Web Developers Work With Data Analysts?

Data Analytics chart

How Learning Data Analytics Can Change Your Life

Ironhack recommended books tech

10 must read Data Analytics books

Python analytics

Help data tell a story with Data Visualization and Python

SQL Databases

Learn the basics of data analytics: Intro to SQL

Panda Python

Intro to Pandas: how to manipulate Data in Python

Ironhack Online bootcamp Python

What is Python? Learn the top 3 best uses for Python programming

Alumni Testimonial Business Analyst

From Sales into Data Analytics, interview with Vincent Laduc (Senior Business Analyst at Google)

Data Analyst

What is the difference between a data engineer, a data scientist and a data analyst?

Data analytics

Tools you must learn as a Data Analyst

Python analytics

Data analysis with Python

differences between data science and data analytics

Data science vs. data analytics

Artificial intelligence

What is Machine Learning?

Data presentation Fifa

What does a data analyst do?

Ironhack Data Analytics

The best data science cheat sheets

Why to use data

How Companies can Build Up their Data Science Competency for the Future

Stay up to date on our latest news and events. Sign up now!
Please type your name
Type your last name
The email is not valid. Please try again

By applying I accept the Privacy Policy and the Terms of Use