Running my own company and creating educational products at KajoData constantly forces me to return to my roots. Recently, while building a new web application from scratch designed to give my students practical hands-on experience with data analysis, I caught myself experiencing a strange feeling. I was connecting the backend to the frontend, setting up a database, configuring user authentication, and leveraging artificial intelligence to push the project forward step by step. At a certain point, I felt a wave of pure, genuine joy—the exact same feeling I had over a decade ago when I was taking my very first steps in the world of technology. Suddenly, something clicked in my mind. I realized why I actually became a data analyst in the first place.
Do you ever have those moments where you live for years believing you made a major life choice for one specific reason, only to realize much later that the real motive was entirely different? Many people entering the IT industry repeat tired formulas: “I became an analyst because I have a mathematical mind,” “I wanted to earn ten thousand more,” or “I was looking for a remote job that would allow me to work from anywhere in the world.” For a long time, I also framed my career in terms of rational professional decisions. However, the truth is that cold calculation is not what led me to become a Data Architect earning twenty-five thousand PLN per month. What brought me here was an almost childlike fascination with building complex systems out of small building blocks.
If you are currently considering a career pivot, thinking about entering the world of data, and searching for an answer as to whether this path is truly right for you, this story might give you a completely new perspective. Analytical capability does not start with sophisticated mathematical formulas. More often than not, it begins with a mundane real-world problem and a healthy dose of constructive obsession.
Erasmus, Cigarettes, and the First Spreadsheet
My journey into data was not paved with diplomas from technical universities. By education, I am a graduate of Polish literature and philology. My humanities studies gave me a strong sense of language, the ability to express complex thoughts clearly, and an understanding of narrative structure, but they had absolutely nothing to do with hard analytics, databases, or software development. Back then, my understanding of numbers, reporting, and financial statements was virtually zero. That was until I went on a university exchange program through Erasmus.
It was during that time abroad, far away from home and structured routine, that I picked up an unfortunate habit—I started smoking heavily. Anyone who has ever been a student living abroad knows that a tight budget can vanish at an alarming rate. After a few weeks, I realized I had zero control over the amount of money I was literally burning away day after day. Buying pack after pack meant that by the end of the month, my bank balance looked terrifying, and I had no clear idea where all my money had gone.
I remembered that I had a program installed on my laptop that almost everyone has heard of, yet few people truly utilize to its full potential: Microsoft Excel. I decided to open a blank sheet and simply start entering every single pack of cigarettes I purchased. I just wanted to gain some level of control over this one leak in my personal finances.
It quickly became clear that tracking cigarettes alone was not enough. Since I was already taking the time to log my habit, the natural next step was to include other daily expenses: food, utilities, going out with friends. Shortly after, I realized that tracking expenses in isolation did not give me a complete financial picture unless I benchmarked them against my income. Around that time, I started picking up various part-time jobs alongside my studies—working in hostels, taking on odd tasks, and assisting guests. My personal budget began to take on a life of its own.
After several months of meticulously maintaining this basic spreadsheet, I experienced a true breakthrough. I realized that manually typing everything over and over again in the exact same manner was tedious and inefficient. If I wanted this file to be genuinely useful, I needed to structure it entirely differently. I redesigned the table layout, introduced distinct expense categories, and created my first automated monthly summaries and reports that allowed me to assess my financial standing with a single click. I wanted transitioning into a new month to be seamless, without requiring me to copy formulas or clean data manually. I wanted automation.
From a VBA Button to My Own Universe: The Birth of Prospero
The word “automation” is on everyone’s lips today, but over a decade ago, it was rarely used in the context of everyday spreadsheets. Searching the internet for ways to streamline my budget tool, I stumbled upon a technology that many today consider a museum relic, but for me, it was an absolute revelation: Visual Basic for Applications (VBA).
I started writing simple macros. My first major challenge was solving the problem of internal account transfers. When I moved money from my savings account to my checking account, the system should not treat it as new income or a fresh expense. It was merely a movement of funds between two sub-accounts, which nevertheless needed to be reflected in my ledger as a credit to one account and a debit to another. Instead of manually inserting two rows and double-checking the figures, I built a simple form using VBA. I could select the bank accounts from a drop-down menu, click a single button, and boom—two rows automatically appeared in the correct places in my table.
Someone might say, “Kajo, modern banking apps do all of this automatically today, why reinvent the wheel?”. That is true. Banks now offer built-in charts and automated expense categorization. But anyone who ever played with Lego bricks as a child, assembled flat-pack furniture, or built their own wooden table in a workshop knows the feeling. The thrill of creating something with your own hands, watching disparate components suddenly fit together seamlessly, is irreplaceable. That was the exact moment I felt the unique spark that would go on to define my entire career.
The true test of this passion arrived shortly after, when I landed my first corporate job in customer service. We worked in an international environment, supporting major commercial banks in the United Kingdom. Our primary responsibility was handling requests related to employee training programs. The ecosystem was incredibly complex—trainings ranged from simple, one-day first aid courses to multi-stage financial certification programs involving dozens of external vendors. Bank employees submitted requests using standardized forms, and we were expected to manually search external websites for matching offers, check availability, verify pricing, and draft response emails.
None of us had been trained in systems engineering or process design. Most of the team simply read the incoming forms, clicked through various websites, and drafted emails from scratch. The process was tedious, error-prone, and highly repetitive. One day, I decided I could no longer work that way. I set out to build an Excel file that would automatically pull available offerings from our database. By simply copying the entire contents of an incoming form (a quick Ctrl+C and Ctrl+V into a specific tab), the tool would generate a fully formatted, ready-to-send email response complete with the matching product and pricing in another tab.
I built this file after hours. I dedicated my personal time to experimenting with formulas, data structures, and macros. My colleagues looked at me like I was crazy, asking, “Why are you doing this? Nobody is paying you extra for it!”. Yet I built this operational system, and I became so obsessed with it that I even gave it a name—I named the file Prospero, after the powerful sorcerer from Shakespeare’s The Tempest.
Looking back today, I recognize a fair amount of youthful cringe in that choice. But that personalization, creating a sense of lore around the project, and viewing code as a form of magic that brings order to a chaotic process gave me tremendous momentum. Prospero did not just grant me immense autonomy in my daily role and lead to a swift promotion; it taught me a core lesson: building reporting systems is an art of stacking blocks that yields pure, unadulterated satisfaction. If it had not been for that single spreadsheet created after hours, I would never have become a Data Architect. I would never have reached a salary level of twenty-five thousand PLN. My background in Polish literature certainly offered no guarantees of getting there.
(At this point, it is worth taking a short pause. If reading this story makes you realize that your current job lacks structured systems, and you want to learn how to build tools that automate chaotic data workflows, take a look at what I have built at KajoData. And if you are looking for a complete, structured roadmap from the fundamentals all the way to landing your first job in data, check out KajoDataSpace. It is a comprehensive subscription program where we guide you through SQL, Python, Power BI, and the core logic of data analysis, complete with access to a vibrant community and experienced mentors).
What Data Analytics Really Is: The Tip of the Iceberg
The story of Prospero brings us to a crucial insight regarding the true nature of the data analyst profession. There is a widespread and damaging misconception among the general public that data analytics is simply about creating spreadsheets and drawing pretty dashboards in Power BI or Excel.
That is a fundamental misunderstanding. Charts, dashboards, and colorful visual reports are merely the tip of the iceberg. They represent only the final slice of our work—the part that a manager or client ultimately sees. The real magic and essence of this profession happen beneath the surface. The vast majority of a data analyst’s work revolves around designing, building, optimizing, and maintaining data delivery systems.
At its core, the entire IT sector is built around creating telecommunication and information systems. Different roles in tech simply specialize in different variations of those same systems. Software developers build systems centered around application logic and business process automation. Data analysts and data architects build systems focused on reporting, data cleaning, modeling, and deriving actionable insights.
The best analysts on the market are not those who have memorized fifty obscure functions in Python. The best analysts are those who understand that their work forms part of a broader ecosystem. The true craft lies in architecting data pipelines and reporting frameworks that are robust, scalable, and easy to maintain. A critical part of this system also includes communication—engaging with business stakeholders, managing tickets, understanding end-user needs, and connecting dots across different departments within an organization.
This is why debating whether a specific tool or language—such as VBA or Excel—is still relevant in the era of advanced artificial intelligence misses the point entirely. Tools will always evolve. Today we rely on SQL, Python, Snowflake, or dbt, and tomorrow we might be orchestrating complex AI agents through natural language. What remains constant is your ability to think in systems. What truly matters is whether you possess that engineering, slightly nerdy drive that impels you to dig into a problem until you discover an elegant, logical solution.
Money, Comfort, or Passion? What Truly Drives You Forward
When I talk to individuals who are looking to switch careers and transition into the data industry, I frequently encounter two distinct types of motivation. The first is rooted in a belief about personal traits: “Kajo, I have always enjoyed working with numbers and I have a strong analytical mindset, so this must be the right job for me.” The second type of motivation is purely pragmatic: “I want to increase my income by ten thousand PLN, work from home in my slippers, and enjoy job stability.”
Both of these reasons are completely valid. There is nothing wrong with wanting to improve your financial situation or seeking a comfortable work environment. I personally value financial stability and the flexibility that working in technology provides. However, based on my seven years of industry experience, I have learned one undeniable truth: relying solely on the desire for higher compensation will not take you very far.
Every job, no matter how exciting it may seem from the outside, comes with its share of frustrating tasks. As a data analyst, you will face days where you spend eight straight hours hunting down a syntax error in a complex SQL query, cleaning corrupted database entries, or explaining the exact same metric for the tenth time to a manager who lacks basic data literacy. Even in my current role, recording YouTube videos or writing blog posts for KajoData, while I love the act of sharing knowledge, I know that recording is followed by hours of video editing, rendering, writing copy, and analyzing viewer retention metrics.
If your sole driving force is money, you will quickly burn out when hit with inevitable roadblocks. What truly sustains you through challenging moments and builds real expertise is genuine passion—that distinct spark of excitement. It is the state of feeling immense satisfaction from the process of solving a complex puzzle. It is the spark that inspires you to name an Excel spreadsheet after a Shakespearean character after hours because you feel you have built something truly valuable.
It is this unassuming passion, this nerdy drive for building systems block by block, that can take someone with a degree in Polish literature and turn them into a Data Architect. High earnings and career flexibility are simply the natural side effects of becoming exceptionally good at what you do. And you only become exceptionally good when you derive genuine pleasure from the work itself.
Summary
Looking back at my career path—from tracking cigarette purchases on Erasmus to building the Prospero tool in customer support, and ultimately designing data architectures and software applications at KajoData—I see one clear, unifying thread. Data analytics has never been merely about manipulating numbers. It was, and continues to be, the practice of understanding reality and structuring it into clear, elegant systems.
If you possess even a fraction of that curiosity, if you enjoy figuring out how different moving parts connect, and if you feel a sense of accomplishment when turning chaos into a clean framework, then the data industry is a place where you can truly thrive. You do not need a degree in computer science or advanced mathematics. You simply need to start laying your very first building blocks.
Thank you for taking the time to read this story. If this article gave you a new perspective, inspired you, or if you think it could help someone you know who is considering a career change and exploring their path in IT, please share it on your social media platforms. Sharing this post on LinkedIn, Facebook, or Twitter helps me reach people who want to build a conscious, fulfilling career in the data world. See you in the next post!
The article was written by Kajo Rudziński – analytical data architect, recognized expert in data analysis, creator of KajoData and polish community for analysts KajoDataSpace.
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