Second year. Two modules on analytics. And I’m sitting in class learning the name of something I’ve been doing by instinct for a year. The self-taught vs classroom contrast — theory vs muscle memory, corporate prep vs freelance reality.
I knew this was coming.
When I decided to teach myself data analytics in my first year, I knew that eventually the degree would catch up to the things I’d already been doing. I knew I’d sit in a lecture one day and recognise everything being explained. I made peace with that before it happened.
What I didn’t expect was how interesting it would feel when it actually did.
The lecture that started this thought.
We’re in class. The lecturer is walking us through the role of Business Intelligence and Information Systems within a corporate structure. In an interactive session, everyone picks a business, and every question she asks, you answer through the lens of that business. Good format. Keeps you engaged.
And as she’s explaining, she introduces the DIKW hierarchy. Data, Information, Knowledge, Wisdom. The framework that describes how raw data moves through a system until it becomes something a business can actually act on.
I’d never heard it called that. But the moment she put it on the board, I thought, I’ve been doing this. Every time I open a dataset, clean it in pandas, run it through a SQL database, build a pipeline that automates the whole thing and spits out a visualisation in Power BI or Tableau, that’s DIKW. I just never had a name for it. It was muscle memory, not a framework.
That’s the weird part. Hearing the name of something you’ve been doing without knowing it had a name.
Theory first, tools later. The classroom way.
We’re still on chapter two. No tools yet. No datasets. Just frameworks, definitions, corporate structures, how a BI team fits into an organisation, who reports to whom, what the project manager’s role is, why deadlines exist the way they do.
I get why it’s taught this way. You need the foundation before you build on it. And to be fair, the theory is filling in gaps I didn’t know I had. When I was self-teaching I was doing things because they worked, not always because I understood why they worked. Class is giving me the why. And when the why clicks, it’s a proper aha moment, not because it’s new, but because it connects something I’ve been doing practically to a reason I never stopped to think about.
But when I was at this same stage, teaching myself, I was already building pipelines from scratch. Python, pandas, SQL databases, Google Analytics, GTM, Power BI, Looker, Tableau. Doing the thing first and working backwards to the understanding. The classroom does it the other way around. Both work. They just feel completely different.
The corporate lens through which everything gets filtered through.
Here’s the thing about how analytics gets taught in a university setting, everything is framed around working in a corporate environment. Every example, every scenario, every piece of advice about communication and deadlines and stakeholder management is built around the assumption that you’re going to join a team somewhere and work your way up.
Which is fine. That’s where most people end up.
But when you’ve spent a year watching freelancers on YouTube, learning from people who built things entirely on their own, the corporate framing sits a bit awkwardly. The idea of being one person on a data cleaning team, doing only that, all day, until you work yourself up to team lead, that doesn’t excite me. What excites me is building a pipeline from nothing and watching it become a fully automated system. That’s not usually what corporate BI analysts do. Each person has a role and that’s their lane.
I’m not saying that’s wrong. I just know it’s not where I’m going.
What actually matters at the end of it.
If I’m honest, the degree gave me this in the first place. Being in school is what exposed me to the field. Without that, I might never have found it.
And the classroom isn’t teaching me nothing, it’s teaching me the theoretical backbone behind everything I’ve been doing on instinct. That’s valuable. I just can’t pretend it’s the only way to get there.
Self-taught and formally educated are just two different doors into the same room. What matters is whether you actually end up knowing the thing, whether that shows up as a job, a client, a project, something real. The path matters less than the output.
I knew I’d be ahead of my peers coming into second year. I made peace with that. What I didn’t expect was how much I’d still be learning, just differently. Less about the doing and more about the understanding behind the doing.
That part has been worth showing up for.
Until next time — ponder this:
Are you learning the thing, or just learning about the thing? And do you know the difference?