Violet’s Career Switch to Data Analytics

1) Can you please introduce yourself and give an insight into your background?

My name is Violet, and I’m 35 years old. I am originally from Serbia and have lived and worked in Belgium for the past ten years. After my studies, I joined my partner in Brussels, where I got the opportunity to work in a freight-forwarding/e-commerce company. I’ve changed a few other companies, gained experience in data management, project management, and logistics, and met some great people along the way.

I fell in love with Brussels and its diversity and opportunities, so I decided to call it my new home!

2) What made you decide to attend a Le Wagon Data Analytics bootcamp?

After my last contract ended, I took some time to focus on what I love doing – playing with data! It connects all my previous roles and what I enjoyed working on the most. I liked working with various departments and helping them with reports used to gain insights and make decisions. I have always been interested in digging deeper and getting information from the “source,” but I haven’t had the opportunity to gain the skills needed to do that.

I started learning by myself, taking online courses, but then I found an “all-in-one” package offered by Le Wagon. The 9-week Data Analytics Bootcamp covers the technical, business, and statistical basics needed to get a good understanding of what all data professionals are doing, so it was a perfect match for me.

3)Can you tell us about your experiences at Le Wagon? Were there any specific aspects of the program that stood out to you?

I had a very positive experience. There were some good and some not-so-great days, but after every day, you gain insights and learn new things. The program is well-balanced, and even if some things are unclear initially, they will come a bit later. Many things are connected and practiced throughout the program, making it much easier and more understandable in the end.

The thing I really liked is that the program covered not just technical parts, but also good practices and understanding of how to handle different stakeholders’ requests. I find this an important part of the job of a Data Analyst as a good understanding of the business needs is a crucial base for any analysis.

4) How did the hands-on projects contribute to your learning experience?

Doing the group projects gave us a sense of what our future jobs could look like. We had the opportunity to practice transforming and preparing data, visualizing the findings, and presenting them to the audience. But also learning and practicing teamwork, communication, and receiving feedback.

For the final project, we used our newly acquired technical and soft skills and organized the team tasks to deliver the results quickly. It was intense, but it pushed us all to give our best and make the final presentation on time and with good results.

5) Did you find the Le Wagon community and networking opportunities valuable?

Absolutely! The community is what makes the whole experience even better. The teachers are professionals who helped us learn but also created a positive and trusting atmosphere. There were many social events that brought us all closer and gave us even more motivation.

As networking is one of the most important things to do when searching for a new job, I liked that Le Wagon thought about us – even after the bootcamp – and organized the Career Week.  During this program, we met alumni, learned how to create a portfolio, and what to expect in the pursuit of our new jobs. In addition, we had the opportunity to talk with recruiters and better understand what companies are looking for.

6) What advice would you give to someone considering enrolling in the Le Wagon Data Analytics bootcamp?

This bootcamp is a good choice for anyone considering pursuing a career in data-related roles. In these fast-changing times when many companies turn to data and digital solutions, getting a good base in just nine weeks is a great option.

It gives a solid understanding of tools and processes. Still, it’s important to keep learning and developing as technology evolves fast, and the need for data literacy constantly increases.