How a Leading Nordic Energy Company Saved 10 Hours a Week on Metadata with Decube

Energy & Utilities

Nordics

A leading energy company in the Nordics transformed fragmented metadata into discoverable, well-described data products, onboarding 500+ users while saving roughly 10 hours a week on metadata work.

Key outcome
10 hours saved weekly

Roughly 10 hours saved per week on metadata work

Decube modules
Metadata Management
Data Products Marketplace
Custom Attributes
Regulatory driver

Danish Energy Agency DEM

The challenge

As the company pushed to make data a shared asset across business and engineering teams, its existing metadata setup could not keep pace. Out-of-the-box catalog fields captured generic technical detail, tables, columns, types, but not the business context that determined whether a dataset was fit for a given use case. Analysts and engineers who wanted to build on existing data assets, or feed them into emerging AI agents, had no reliable way to tell what a dataset was for, who owned it, or how current it was, without asking around.

Enriching metadata to answer those questions was a manual, recurring task split across the data team, consuming hours every week that could have gone into higher value work. With growing internal demand for self-service access to trusted data, from business teams and from AI agents alike, the company needed a way to package data as discoverable, well-described products rather than raw tables.

The solution

The company adopted Decube to build a data product marketplace, a curated layer where data products, not individual tables, are packaged, described, and made discoverable to both technical and business users.

The centerpiece of the rollout was Decube's custom attribute framework. Rather than settling for a fixed metadata schema, the data team defined attribute fields specific to its own business processes, letting product owners tag and enrich each data product with the classifications, ownership detail, and business context that mattered internally. That flexibility meant the marketplace could evolve alongside the business rather than forcing teams to adapt their processes to the tool. As adoption spread, the marketplace became the default place both people and internal systems went to understand data context, including the AI agents now consuming that same metadata to reason over the company's data.

Results in practice

A self-service data product marketplace

More than 500 users across the business have been onboarded onto the marketplace, using it as their entry point to find, understand, and trust the data products relevant to their work.

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Custom attributes built around real business processes

Rather than being limited to generic catalog fields, the data team used Decube's custom attributes to model metadata the way the business actually thinks about it, cutting the back and forth that used to accompany every new data product and reducing manual enrichment work by roughly 10 hours a week.

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Metadata that now feeds AI agents, not just people

The same enriched context that powers the marketplace for human users is also feeding internal systems and AI agents, giving them structured business context to reason over rather than raw, undocumented tables.

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The outcome

The data product marketplace now saves the data team roughly 10 hours a week that used to go into manual metadata enrichment, time redirected into higher value data product work. On the adoption side, more than 500 users are actively onboarded and using the marketplace as their front door into the company's data, a scale that would not have been realistic under the old model of ad hoc requests and manually maintained documentation.

“We did not want a catalog that just listed tables. We wanted something our business teams, and now our AI agents, could actually trust and use,”

said the company's Data Product Owner.

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