An Introduction to Common Sense
...Data
What’s all this, then?
Hello world, and welcome to Common Sense Data! This is where we’ll figure out today’s most burning questions related to all things DATA, unfazed by hype or tech vendor jargon!
Tired of guessing if Metapod should be a key part of your postmodern data stack or a key part of your Pokemon deck?1 Tired of all the icebergs, lakes, streams, and other hydrological terms? You’ve come to the right place! We’ll take a step back from all that and focus on the bigger picture.
On this Substack I try to distill from all the noise you see - on LinkedIn, YouTube, and all the data conferences around the world - the core: the Common Sense, the magical Golden Path of ideas, patterns, and concepts that just simply make sense.
Many years ago, I was sitting in a cafeteria of a large corporation with my then-client’s data lead, and we were shaking our heads at some new insanity we had just discovered in that organization. “You know,” the data lead said, “countless people have done this stuff for decades in a myriad organizations. You’d think it isn’t that hard to figure out the basics, but here we are again!”
Yes, we keep getting into all kinds of trouble with the same things over and over again. Technology keeps advancing, sure, but the real roadblocks and bottlenecks tend to be the same. You’d think it isn’t that hard. But it is! And one reason it is hard, I think, is because we in the data business keep producing endless content on tech-du-jour topics, and how to remake your platform for the Nth time, and how to move from Iceberg to Delta to Caterpie2, but what we seem to lack is some… common sense.
The Common Sense approach (look, I capitalized it - new buzzword!) I’m setting up here is basically all about walking on a tightrope between:
a) being completely technology-agnostic, to a degree that we’ll just shrug at the MAD landscape and all the Gartner Magic Quadrants, and
b) being unashamedly practical, even at the risk of drawing the ire of crowds of people waving their fingers in unison and saying “ackshually” because I didn’t follow an accepted theory.
The point is to figure out not necessarily how a solution should be implemented, but how we should think about it so that we can better understand why we’re implementing it the way we do.
Another thing I want to point out right off the bat is that this is also going to be an intensely opinionated and personal collection of writings. I will write it as I see it. You don’t need to agree - in fact, we’ll probably both learn more if you don’t, and instead you come to the comment section to point out my mistakes! (in a constructive fashion, hopefully)
Now, you will probably have a few questions in mind about my approach and how dare I call it “Common Sense” when it clearly isn’t common and frankly it isn’t very sensible either, and rest assured, those questions (or some questions at least) will be answered soon… but first, a few practicalities.
Who am I?
Well, hello again! I’m Juha.
That’s me, photographed during the 2024 Helsinki Data Week (more about that in a bit).
The full name’s Juha Korpela. For the native English-speakers there, and possibly some others like the French, it’s easier to think of it as ‘Yuha’, and you’ll get the pronounciation correct enough. It’s a Finnish name - I live in Helsinki, Finland. You can find me on LinkedIn as well.
I’ve been in the data business for about 15 years at the time of writing this. Initially started in the public sector, working on business registry and related stuff at Statistics Finland. Did a few years in a consultancy, jumped ship to a large manufacturing corporation, hopped over to a startup, and in late 2023 thought to myself, “you know what J/Yuha, maybe it’s time to go solo”, and I did!
My one-man consulting company, Datakor Consulting Oy, has been running for almost two years now. I’ve worked with super-interesting clients mainly in large-ish corporations in Finland, but have also done speaking gigs and training sessions and whatnot abroad. Mostly this work has been about data models, high-level architecture, and more recently data products (i.e. product management approach in data - more on that in later posts!).
I am also one of the founders of Helsinki Data Week, which is our very own indie data conference, first held in 2024 and soon coming back in October 2025. I’m incredibly lucky and grateful to work on that with my dear friends Eevamaija Virtanen, Säde Haveri, and Antti Rask on that - love you guys! If you want to hear what I and the rest of that crew sound like, you can check out our podcast Helsinki Data Mafia on Spotify.
Anyways, through all this time, since my 2nd day at Statistics Finland when my boss asked “hey, have you heard of this thing called a ‘Data Warehouse’” and I said “uhhh not really” and he said “well start googling because you’re in a Data Warehousing project”, I’ve been really keen on two things:
Figuring out what is the right way to do things - not just how to get this one project finished, but how all of this should be thought about, and
Data modeling.
Yes, I happen to think data modeling is pretty much the most fun one can have with one’s pants on. And not just any data modeling - conceptual data modeling, the part where you talk with the actual business and try to figure out what their data is actually about! But more on that later (trust me, there’s going to be quite a few data modeling related posts).
One more thing about me that is rather relevant, I feel, to this Substack: I like writing. Writing is a way for me clarify my thoughts, and to express myself, to explain my thinking process to others. That’s why I always write every single word myself. No AI here! I’m no luddite - I will probably generate some pretty pictures occasionally, or check if a certain phrase makes any sense in English (after all, this is my 2nd language) and so on, but the text is mine and mine alone. Even the dashes! 100% artisan hand-crafted posting, with all the rough edges that come with it.
How’s this going to work going forward?
I like to think I’m pretty good at planning. One of my favourite quotes is from Dwight D. Eisenhower, the commander of SHAEF (i.e. the big Allied boss in World War 23) and later US president:
“Plans are useless, but planning is indispensable.”

My plan is to write one of these long-ish form posts once a week. There will be posts focusing on some specific topic, such as data modeling, where I think I have something useful to say. I have a list of such topics waiting, even! There will also be posts where I will simply grab onto something that’s currently causing a ruckus on LinkedIn, or something that I have run into during a conference or in a discussion with other data folks. These sorts of ad-hoc posts might appear more or less frequently in between the more considered, “serious” topics.
Topics that I want to cover include, for example:
data modeling (obviously) and semantics
operating models (centralized, federated, decentralized etc.)
metadata management of all kinds
overall a focus on outcomes, not output
But likely this Substack will start some way and then evolve into some other direction. Hopefully, it’ll go in a better direction, like some fancy Pokemon4 evolving into an even fancier Pokemon. I’d like to think that to a large degree that direction also depends on you, dear reader - you can like and subscribe and whatnot to let me know you’re actually reading this, post comments to let me know where I made sense and where I didn’t, and also suggest further topics that would benefit from a bit of Common Sense. Then I’ll update my plans accordingly, like Eisenhower!
However, my plan is not to try to make lots of money out of writing this. There’s no subscription fee: just subscribe if you’d like to be reminded about new posts and all that. Maybe at some point in the future, if the Pokemon has evolved sufficiently5, I’ll figure something out in that direction - but the point is to write my thoughts down in such a way that they will hopefully help someone along in their data career, and to also help me to think more clearly and to find out what the Common Sense we’re so much lacking really is.
There we go.
If you made it this far, thank you! I’m grateful that you’ve chosen to spend your valuable time reading my ramblings, and I’m hoping we’ll be co-rambling together in the future. Hit the subscribe button (hold on, where is it… oooh there we go), share this to your friends (or enemies, depending how you liked it), find me on LinkedIn, and let me know what you think!
Until next time: cheerio!
It’s a Pokemon, but damn, if I were to start a podcast on metadata…
You probably guessed that this is a Pokemon.
Beyond data-related things, the 3 biggest interests in my life are jazz, cocktails, and WW2 history. Yes I know it sounds a bit snobbish and very “middle-aged white guy”, but it’s hard to avoid that a, what with me being a bit snobbish middle-aged white guy!
Metapod, by the way, apparently evolves into Butterfree. Honestly I don’t really know anything about Pokemon, and I enjoy real butter in my food thank you very much, but I just wanted to point that out. I swear I’ll avoid Pokemon references in the future.
Argh



Hey @Juha Korpela ! Really excited to read this Substack. As an analytics engineer who has pretty much had to started his career with the “modern data stack” world, super keen to get in touch a bit more with the foundations of data.
Also, love the humour :)
Love the footnotes! Looking forward to reading your thoughts here, Juha.