"Google is your best friend"
Over the past years, I’ve worked with many different data platforms and techniques. Yet somehow, one thing has always remained the same: the three-layered data architecture that underpins every data platform.
In this blog series, we’ll uncover this recurring pattern and explore why we keep designing our platforms this way. Each part dives into a different perspective, ultimately revealing the similarities and the real value behind a three-layered data approach.
We’ll kick things off with Part 1, where I reflect on my own data journey to answer a simple but surprisingly tricky question: what is Business Intelligence, really?
My Data Journey
My data journey started 13 years ago.
Fresh out of Tilburg University, I kicked off my career as a consultant. And over the years, I’ve had my fair share of memorable moments across different clients.
From building my very first Data Vault data warehouse… to suddenly becoming “the SOX BI guy” at a well-known retail company. Somewhere along the way, I even took a short detour into AWS, but let’s be honest, it didn’t take long before I found my way back home to the Microsoft stack, where I now focus on Microsoft Fabric.
But despite all those experiences, there’s one moment that still sticks with me.
On my very first day as a consultant, right after graduating, my manager walked up to me and said:
“You are going to do BI!”
Wow… what a warm welcome! 😄
But do you know what my actual response was?
“Uh… wait… WHAT?!”
I genuinely had no clue. I didn’t know what BI was.
At university, the term simply never came up. And that’s pretty surprising, considering I had just finished a master’s in Econometrics and Operations Research…
So after the introduction day, I did what everyone did back then: I started Googling.
There was no Copilot yet, in those days, Google really was your best friend.
Search your question, get your answer. Simple as that.
So I did, trying to prepare myself for my first BI assignment. Step by step, I started to understand what a “traditional” BI solution looked like.
But that still leaves the big question…
What is BI, actually?
Let’s dive into a bit of history.
What is BI?
Before BI had a name, the rise of computers already changed how we handled data. Early systems, known as Decision Support Systems (DSS), started helping organizations store and analyze data as early as the 1970s.
The problem? These systems were slow, complex, and lacked a clear business purpose.
The turning point came in 1989, when Howard Dresner (Gartner) introduced the term Business Intelligence as an umbrella concept. From that moment on, BI got a definition and meaning. Let's put the definition here.
BI Definition:
In 1989, Howard Dresner proposed business intelligence as an umbrella term to describe
"concepts and methods to improve business decision making by using fact-based support systems."
It was not until the late 1990s that this usage was widespread.
According to Solomon Negash and Paul Gray: " Business intelligence (BI) can be defined as systems that combine:
- Data gathering
- Data storage
- Knowledge management
with analysis to evaluate complex corporate and competitive information for presentation to planners and decision makers, with the objective of improving the timeliness and the quality of the input to the decision process.”
Business Intelligence has evolved significantly over the decades, from early structured reporting to advanced analytics. In the 1980s, the focus was on sharing insights through basic reports, followed by the 1990s with data warehousing and OLAP enabling deeper analysis. The 2000s brought BI into daily decision-making through dashboards and reporting tools. In the 2010s, self-service and cloud made BI faster and more accessible than ever. Today, in the 2020s, AI and machine learning drive predictive insights and smarter, automated decisions.
Nowadays, you can simply ask Copilot for a definition of Business Intelligence. No more endless Googling!
And within seconds, you get a clear and structured answer.
So, what does Copilot tell us?
It gives us a modern, refined view on what BI really means today.
Let’s take a look at what I like to call and see the answer from copilot:
The Best Business Intelligence Definition
"Business Intelligence (BI), is the practice of turning raw data into meaningful insights that support better, iaster, and more informed decision‑making.
It combines data integration, analysis, and visualization to give organizations a clear, real‑time picture of what’s happening, why it’s happening, and what to do next.
Business Intelligence turns data into insight, and insight into better decisions."
Which is a really interesting definition!
What's nice to see is how these definitions compare with each other, the one from 1990 and 2026.
Historic BI Definition
Data Gathering
Data Storage
Knowledge Management
Analysis
Presentation
Copilot 2026 BI definition
Integration
Raw Data
Meaningful insights
Analysis
Visualization
You know what’s funny about this?
After 35 years, it’s basically still the same.
Yes, we now have Copilot, AI, and all kinds of new technologies.
But if you look at the core, the definition has not really changed at all.
And honestly, I like that.
It means the foundation was already strong. We just got better tools to work with it.
But here is the interesting part.
There is actually more behind this......
You will find out in part 2 soon!