Are Data Teams and Business Users Really at Odds?
Allan WillePublished 2026-04-01Summary: There's a running joke that pits data teams against business users. But in my experience, the friction isn't really about personalities — it's about one thing both sides keep getting wrong.
I get this question a lot. And it's funny—because depending on who you ask, it can turn into a bit of a debate.
There's a long-running narrative that data teams and business teams are somehow at odds. Different priorities, different languages, different expectations.
But honestly? In most cases I see, they actually work pretty well together.
They just don't always realize where the real collaboration needs to happen. Watch this quick video to see what I mean:
Where things actually connect
Data teams are focused on what you’d expect: data quality, governance, availability. Making sure the data is clean, reliable, and accessible.
On the other side, business teams are trying to make decisions. They need data they can trust—and just as importantly, data they understand.
The overlap isn’t dashboards. It’s not reports.
It’s metrics.
That’s the contract.
When both sides come together to define a metric—what it means, how it's calculated, what data it uses—that's where things click. The data team understands what needs to exist behind the scenes: tables, joins, permissions, pipelines. The business team gets confidence that the number is accurate, consistent, and usable.
That shared definition becomes a foundation both sides can rely on.
Where things break down
Of course, it's not always smooth. A few common issues show up:
- Data teams working in isolation, without enough business context
- Business teams not trusting the data (often for good reason)
- Poor communication leading to mismatched expectations
- Metrics being defined differently across teams
Most of these trace back to the same root problem: the definition of the metric wasn't shared.
This is where things start to scale
Once you do this a few times, something interesting happens. You start building a catalog of metrics—a set of trusted, defined artifacts that everyone agrees on.
That's what actually enables self-serve.
Not more dashboards. Not more tools. But a shared understanding of the numbers themselves.
When that's in place, business users don't need to second-guess the data, data teams don't get pulled into endless one-off requests, and everyone moves faster with more confidence.
What makes it work
The teams that do this well tend to follow a few simple patterns:
- Shared goals – metrics tied directly to business outcomes
- Open communication – fewer handoffs, more collaboration
- Better data literacy – business users understand what they’re looking at
- Feedback loops – metrics evolve as the business evolves
- Clear storytelling – data is presented in a way people can actually use
None of this is revolutionary. But it does require intention.
The bottom line
Data teams and business teams don’t need to “get along better.”
They need to define metrics together.
That’s the unlock.
And the good news is—it’s already happening more and more. When teams lean into this, it works really well.
If you’re in the middle of this right now, I’d love to hear how it’s going. What’s working? What’s not? Any tips or patterns you’ve seen?
Always curious.