All stories

Metsähallitus · Government · Feb 2026

Fragmented data is a leadership challenge — here's how to turn data into a business driver

When key concepts mean different things across systems, trust erodes and decisions slow down. Metsähallitus built a shared conceptual model of 1,400+ concepts with DSharp to make metrics consistent and reusable across teams.

Fragmented data isn't only a technical problem — it's a leadership one. When a word like “area,” “customer,” or “yield” is defined differently in every system, every report needs a footnote, and every decision waits on someone reconciling the numbers by hand.

The challenge

Across a large organization, the same business concepts had drifted apart in each source system. Teams re-derived the same metrics over and over, in different tools, for different questions. Leadership couldn't be sure that two reports on the same subject were even counting the same thing — so the data slowed decisions down instead of speeding them up.

What they did with DSharp

Rather than start with pipelines, Metsähallitus started with meaning. Working in DSharp, they built one shared conceptual model — classifying and defining their business concepts once, in language the business recognizes, and letting DSharp generate the standard, tested structures downstream.
1,400+shared concepts modeled in one place

The outcome

A definition is now written once and reused everywhere. Metrics are consistent and reusable across teams, and the model — not a spreadsheet or a person's memory — is the source of meaning. That's the shift that turns data from a source of doubt into a genuine business driver.
DSharp gave us a single source of meaning. The model is the contract — and everything downstream finally lines up with it.Chief Data Officer · Nordic public-sector organization
Back to all stories

Get started

Want the same for your data?

Book a 45-minute walkthrough. We'll take one of your sources from raw data to a clear, trusted model — live, in your own environment.