What Does a Data Analyst Need to Know in the Age of AI? Jan Šulta on Data, Business, and Studying While Working
15 min. | 30. 9. 2026
Working with data is no longer just about programming, spreadsheets, and choosing the right tools. In the age of AI, the ability to understand business context, critically assess outputs, and define the right problem is becoming increasingly important. Jan Šulta, a data scientist and analyst at Exclusive Networks and a student of the master’s programme in Applied Economics and Data Analysis at Unicorn University, discusses what data professionals need today, how full-time work can be combined with study, and who can benefit most from this type of programme.
You’ve been working with data for several years. What led you to choose Applied Economics and Data Analysis?
The main factor was my work with Exclusive Networks and my role, where data is treated as an internal service for the entire company. That naturally comes with the challenge of switching between the technical and business sides and being able to adapt to working with different departments and stakeholders.
That is why I was looking for a programme with a strong STEM foundation, built around quantitative methods, programming, and technical work with data. At the same time, I wanted a programme that connects the data and business perspectives. Applied Economics and Data Analysis met those criteria. You can also broaden the programme through elective courses based on your own interests. In my case, I chose machine learning and applied optimisation, which became the topic of my master’s thesis.
How well do you think the programme prepares students for what companies expect today in the field of data and analytics?
For me, the most valuable thing you learn in the programme is how to think about data problems from a business perspective and evaluate the best approach, including choosing the right technologies and tools. You can see this clearly in the workshops, for example, where you first have to agree with the others on how to approach the problem before you even start working with the data.
In the age of AI, this matters even more. Technical tasks are increasingly being handled by agents and assistants, which makes it even more important to understand the outputs they provide. You need to be able to critically assess what AI gives you and recognise when its output can be trusted and when it cannot. From an employer’s perspective, this also makes such a graduate valuable because they are able to handle a broader range of tasks.
What surprised you the most during your studies or at Unicorn University? Was anything different from what you originally expected?
First of all, I was pleasantly surprised by how well the programme can be combined with full-time work. I started with some concerns, but in practice, it really works.
Second, I did not expect such a diverse group of classmates. You meet people from different companies and industries, so the discussions are not just theoretical—they are based on real-world experience. I would even say that this networking alone is a good reason to give our university a chance.
What surprised me the most, though, was the quality of the university’s research activities and the way research findings are integrated into teaching. For me, the programme is not just a formal way to add another degree, but a real step forward professionally. The interesting job opportunities I have received since then, both in the Czech Republic and abroad, also confirm that.
Who do you think can benefit the most from the programme, and what roles or career paths can it prepare graduates for?
In my view, it is an ideal choice for anyone interested in Business Intelligence, data analysis, or data science. It can benefit both juniors who need a solid foundation and experienced professionals who want to deepen their knowledge or move into a more specialised role.
Where I see the greatest added value, though, is in managerial positions. The ability to understand data while also grasping the business context is essential for leadership roles. A manager with this kind of background does not make decisions based on gut feeling, but on data they understand themselves.
And for some people, it can go even further. I am currently considering doctoral studies myself, and the quantitative and analytical foundation the programme has given me plays an important role in that.
If you had one minute to convince a prospective student why they should choose Applied Economics and Data Analysis at Unicorn University, what would you tell them?
I would put it simply. I have been working with data for years, and even so, this programme has given me knowledge and skills that would have been difficult to develop on my own. That says a lot.
It is a genuinely technical and analytical programme, not an economics degree with a touch of data. You learn how to think about data systematically, work with quantitative methods and modern analytical tools, while also understanding how the results translate into business decision-making. And you study at a university that is part of the Unicorn technology group, so the connection with real-world practice is not just something that is stated—it is genuinely there.
As a graduate, that sets you apart from purely technical profiles and opens doors to areas where demand for data professionals is particularly strong today.
So if you are interested in working with data and analytics, give this university a chance. For me, it is a clear choice.
Are you interested in data, economics, and decision-making in the age of AI?
Apply for our follow-up master’s programme Applied Economics and Data Analysis, which combines advanced economics with practical work with data, data analysis, and interpretation. You will learn to use quantitative methods, modern analytical tools including AI, and work with data in a way that supports informed decision-making in both business and economics.
The programme also includes practice-oriented workshops, teamwork, and solving real-world tasks under the guidance of industry professionals.
