There’s something rather ironic happening in the world of data right now. We’re living in an age where AI can write essays, generate images, and even predict customer behaviour with startling accuracy. Self-service BI tools promise that anyone can become their own analyst with just a few clicks. Yet somehow, the need for proper data skills has never been more critical.
I’ve been thinking about this a lot lately as I prepare for our upcoming Data Analyst training course in Montenegro, which kicks off in mid-January and runs for two and a half months. This isn’t just another training programme—it’s become something of an institution for financial professionals across Montenegro and the neighbouring countries, and for good reason.
The AI Paradox: Why Human Data Skills Still Win
Here’s the thing: AI and self-service tools are brilliant, but they’re only as good as the foundations they’re built upon. You can have the fanciest Power BI dashboards in the world, but if your data model is fundamentally flawed, you’re just automating nonsense at scale. It’s like building a magnificent house on quicksand—impressive to look at, but unlikely to end well.
This is particularly crucial in the financial sector, where our participants typically work. When you’re making decisions about loans, investments, or risk assessments, “close enough” simply won’t do. You need to understand not just what the numbers are telling you, but why they’re telling you that, and whether you should actually believe them.
What We’re Actually Teaching
Our course takes participants on a complete journey, starting from the very beginning with data modelling. This is about understanding how to organise information in a way that makes sense—thinking through what data you need, how different pieces of information connect to each other, and how to structure everything properly before you start building anything.
From there, we work through creating actual databases in SQL Server. It’s hands-on and practical, giving you skills you can use straight away in your work.
Then comes the exciting part—Power BI. This is where everything comes together. Once you understand how data should be organised, Power BI becomes a powerful tool for creating reports and dashboards that actually tell a story. We cover everything from building your first reports to using DAX, which is the formula language that helps you create really useful calculations and insights.
Power BI: More Than Just Pretty Charts
Let me be clear about Power BI—it’s not perfect, and it’s certainly not the only option out there. But there’s a reason it’s become so popular in the business world. Microsoft has created something that’s both powerful for data professionals and accessible for business users who just need answers quickly.
What makes Power BI special is how it works in layers. On the surface, you can create decent charts and graphs quite easily. But when you’re ready to go deeper, you’ll find sophisticated tools for working with data, creating complex calculations, and connecting to almost any data source you can think of. It’s a tool that grows with you as your skills develop.
What I particularly like is how Power BI encourages you to think properly about your data. Unlike Excel, where you can sometimes get away with messy spreadsheets, Power BI rewards good organisation and structure. It’s both a learning tool and an analysis tool at the same time.
Why This Training Works
Over the past few years, we’ve welcomed participants from financial institutions across Montenegro and neighbouring countries. There’s something special about bringing together professionals who share similar challenges but approach them from slightly different angles. The discussions during breaks, the questions that spark new ideas, the connections that form—these are often as valuable as the formal training itself.
The financial sector here is evolving rapidly. New regulations, digital transformation, increased competition—all of this means that organisations need people who can not just look at data, but truly understand it. The institutions that invest in this kind of training for their staff aren’t just ticking a box; they’re building a real competitive advantage.
The Human Element in an AI World
So why does all this matter in the age of AI? Because AI is a tool, and tools need skilled operators. When ChatGPT generates SQL queries for you, you still need to know whether those queries make sense. When a machine learning model suggests a particular segmentation, you need to understand whether the underlying data supports that conclusion.
The real value in modern data work isn’t in performing routine calculations—computers are far better at that than we’ll ever be. The value is in asking the right questions, understanding context, spotting anomalies, and translating technical findings into business language. These are fundamentally human skills, and they’re built on a solid foundation of data knowledge.
Looking Ahead
As I prepare for January, I’m excited about this new group. The financial industry is at a turning point, where the organisations that can use their data effectively will move ahead, whilst those that can’t will struggle. Our participants will leave with skills they can use immediately, but more importantly, they’ll have a way of thinking about data that will be useful throughout their careers.
If you’re working in Power BI and want to learn more about DAX specifically, have a look at my book, “Mastering DAX in Power BI: Your complete roadmap to DAX mastery in Power BI”. It takes you from the basics right through to advanced techniques, with plenty of practical examples.
Mastering DAX in Power BI on Amazon
The course might be here in Montenegro, but the lessons apply everywhere. Whether you’re working in a bank in Podgorica or a finance company in London, the fundamentals of good data work are the same. And in a world that’s increasingly driven by data, those fundamentals have never been more important.
See you in January.