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Ever crashed a warehouse with one query? Or presented a dashboard that made the CMO panic? You’re not alone.
In this episode of The Data Crunch Podcast, Helen joins Vadym to share the real, painful, and hilarious mistakes data analysts make — and the critical lessons behind them. From SQL gone rogue to dashboards that double-cross, these stories will make you laugh, cringe, and maybe check your own reports twice.
You’ll learn:
➡️ Start making data-driven decisions with OWOX BI
Vadym:
Hey everyone, welcome back to The Data Crunch Podcast! I’m Vadym from the OWOX team, and today’s episode is going to be a little different — a little messier, a little funnier… and very real.
Because we’re talking about the top data analyst mistakes — the ones that actually happen.
Not theory, not best practices — real, facepalm-worthy stories from the trenches.
And joining me is someone who’s seen more dashboards than most people see movies — Helen, our Head of Customer Success here at OWOX.
Helen:
Hey Vadym! I’m really looking forward to this one. I’d love to keep it light, but let’s be honest — behind every facepalm moment is a real lesson.
Hopefully, our listeners take away a few laughs and a few reminders.
Because the truth is: mistakes happen. And in data — they will happen. The important thing is learning from them… and ideally not repeating them on a loop.
Even better? Learn from someone else’s mistakes before they become your own.
So today, I’ll be sharing a few real-life stories — from our clients, our team, and, yes… even some from my own experience.
Vadym:
Exactly. So if you’ve ever broken a dashboard, crashed a warehouse, or copy-pasted the wrong forecast into a board deck — you’re in good company.
And hey — if you want fewer fire drills and more confidence in your analytics, we’ve got your back at owox.com. Just book a free demo and let’s clean things up together. And don’t forget to subscribe to our YouTube channel to get more episodes like this.
Alright Helen, let’s get into it. What’s our first story?
Helen:
For starters, I wanna share with you a story that I call “SQL That Crashed the Warehouse.”
Picture this: an analyst writes a SELECT * on a 50-billion-row table… joins without filters… and hits RUN.
The warehouse locks up. Latency spikes. Other jobs fail. Panic.
And the kicker? They didn’t even need all those columns — they just didn’t want to scroll.
Vadym:
Oof. The “I’ll clean it up later” approach.
This is why warehouse costs go through the roof and your Friday turns into a fire drill.
Also: defaulting to SELECT * should be considered a minor crime
Helen:
Couldn’t agree more.
So, here’s a quick reminder list — simple, but battle-tested:
And look — yes, some of these tips might sound too obvious. But that’s exactly the point.
Ask yourself honestly: do you just know these things… or do you actually follow them every single time?
Vadym:
Alright, next up is what I like to call “The Dashboard That Lied.”
Here’s one we’ve all seen: two teams, two dashboards, both showing ROAS — but with slightly different definitions.
CMO pulls up both dashboards during the meeting. One says ROAS is 12. The other says it’s 0.3.
Silence. Eyebrow raises. Budget panic.
Helen:
I’ve actually been on a call like that. You hear:
“Wait, why is ROAS so different?”
“Well… what’s your formula?” “Same as yours. Should be”
And now it’s a showdown between Marketing and BI.
Vadym:
This is why defining metrics once, documenting them, and reusing them across all tools is so important.
Because in the end, the real problem isn’t the metric — it’s the trust.
Helen:
Totally.
So, two simple tips to keep your dashboards honest:
Trust me — future you will thank you.
Vadym:
Speaking of dashboards and what happens after you share them…
Let’s talk about what I call “Copy-Paste Chaos.”
You build a dashboard. It works, it’s solid, everyone loves it.
Then someone copies it, tweaks a few filters, adds a join, maybe changes a formula here and there… but leaves the original data prep untouched.
Helen:
Yeah, and the next thing you know — the numbers are off, stakeholders are confused, and guess who gets the Slack ping? Yep — you.
Because hey, you made the original one, right?
Vadym:
That’s the moment your soul leaves your body.
Helen:
Oh, this is too real.
Once you create version one, you become the unofficial support rep for every version that follows. You hear: “We just reused your dashboard!”
Cool. But now it’s misreporting conversions and attributing everything to ‘(not set)’.
And suddenly, you're the proud parent of a dashboard monster you didn’t raise.
Vadym:
Put that on a mug, a hoodie, and the onboarding checklist.
But seriously — copying dashboards isn’t bad. It’s how teams move faster and avoid reinventing the wheel.
The key is: do it consciously.
Here are a few easy habits that make all the difference:
Helen:
You don’t need to be afraid of dashboards or reusing Data Marts. It’s like using the recipes. If you change the ingredients, taste-test before serving them to the execs.
Vadym:
Alright, next story is called — “When You Trusted the Business User.”You get a dataset from the client. You build the dashboard with this data. Everything looks great.
Then, a few weeks later — the CFO opens it… and finds missing revenue, messed-up costs, and a bunch of rows labeled “test.”
Helen:
Yep. Been there. Over time, source tables change: columns get added, formats shift, and data gaps sneak in.
And the dashboard? It doesn’t magically adapt.
Still, the first thing we hear is: “Your dashboard is broken.”
Not: “Maybe something changed on our side.”
Vadym:
According to our very unofficial stats — only about 8% of clients actually go back and check their data before blaming the report.
Helen:
So, the advice is super simple:
Even if the data was clean before — always re-validate when something looks off and start with the source.
Even if they swear nothing changed.
Especially when they swear nothing changed.
Vadym:
Because “we checked it once” does not mean “it’ll stay correct forever.”
Okay, ready for a mistake so common it should have its own holiday?The “VLOOKUP of Doom.”
You use VLOOKUP… but forget the “FALSE” parameter. So it matches the “closest” value.
Suddenly, 10 customers have the wrong account manager.
Helen:
This one hurts because it feels like it’s working.
No red flags, no obvious issues — just broken assignments and silent chaos.
Tip of the day? Either switch to XLOOKUP, or stop pretending spreadsheets are a reliable place to do joins.
Helen:
Alright — and finally, one of my personal favorites: “When You Modeled Too Hard.” You get a task: build an attribution model. And somewhere in the brief it says: “Let’s make it machine learning-based — that’s what everyone’s doing now.” So, you go all in — 17 weightings, 4 macros, 2 sleepless nights, and a sprinkle of machine learning magic.
It’s smart. It’s sophisticated. And then... the team keeps using last-click anyway.
Vadym:
Yeah — and what we’ve seen time and time again is this: It’s not about how complex the model is under the hood. What really matters is how the team actually works with the output.
Helen:
Exactly. So if you've got that kind of request — try offering two versions: One more advanced, one more simple. Then just see which one gets used in the weekly marketing meeting — that'll tell you everything.
Vadym:
But hey — if the team does consciously choose your masterpiece over last-click… that’s your sign to ask for a raise.
Because it means you don’t just build brilliant models — you actually know how to implement and explain them. And that’s a rare superpower.
Helen:
So here’s the bottom line: Mistakes happen.
The key is building systems and cultures that help catch them early — or avoid them next time.
And if you want fewer messes, better tools, or just a second pair of eyes — we’re here for that.
OWOX helps teams move from fragile spreadsheets and fire drills to confident, clear reporting — at scale.
Vadym:
Exactly. If you want more trust and less troubleshooting, check us out at owox.com.
We’d love to help you clean up your analytics — and maybe avoid your own “VLOOKUP of Doom.”
Thank you, Helen, for sharing your stories. Thank you guys for listening. Share this episode with a fellow analyst who needs a laugh — and don’t forget to subscribe to our YouTube Channel to get more valuable content like this.
We’ll see you next time on The Data Crunch Podcast!
