How the numbers work

Everything on DataImpactor is calculated from open Danish public data and refreshed automatically. Here is exactly what goes into it.

Where the data comes from

• Businesses - the Central Business Register (CVR) from Datafordeleren. We count production units (P-units): the physical places where business happens. A café chain with five shops counts five times, where the shops are. Updated weekly in full and daily with changes.
• Business type - each place's main Danish branche code (DB07, and DB25 from 2025), grouped into everyday categories. A business counts in one category only.
• Location - the registered address, matched to the Danish Address Register (DAR) for coordinates and parish.
• Population - Statistics Denmark: quarterly for municipalities and parishes, yearly for postcodes.
• Financials - annual reports filed with the Danish Business Authority (XBRL). Only companies (ApS, A/S …) file accounts; sole proprietorships don't, and small companies usually report gross profit rather than revenue.

Openings, closures and trends

A business is opened on its production unit's start date and closed on its end date. “Active 3 years ago” uses the same dates, so trends can be reconstructed back to 2008.

Company forms and holding companies

Every figure can be limited to company forms with the filter at the top of the page: Enkeltmandsvirksomhed (sole proprietorship), ApS, A/S, I/S and Other (K/S, P/S, IVS, cooperatives, associations, foundations and the rest). Pick one or several; All includes every form. Your choice is remembered on this device.

Non-financial holding companies (ikke-finansielle holdingselskaber, branche code 642020 in DB07 and 642120 in DB25) are excluded from all statistics unless you untick the box. They own shares in other companies and are often registered at the owner's home, so they say little about local demand, but there are well over 100,000 of them.

Financial figures follow the filter too, but only companies that file annual reports have them, mainly ApS and A/S.

Growth and decline

The Trends page lists the municipalities, postcodes and parishes where businesses are growing or disappearing, for all businesses or one business type. 3-year change compares active businesses today with three years ago; net closures is closures minus openings; the closure rate is closures in the last 12 months as a share of the businesses active 12 months ago. Areas need a minimum number of businesses before a percentage is shown, so one closure in a tiny parish doesn't top the list.

Density and similar areas

Density is active businesses per 10,000 residents. Each area is compared with areas of the same kind (municipality, postcode or parish) in the same population band (fifths by size). The expected number is what the area would have at the median density of those similar areas.

The opportunity score (0-100)

A starting point for research, not a guarantee. 50 is average. It combines:

35%	Room in the market, fewer businesses per resident than similar areas
20%	Population growth over 5 years
20%	Momentum, net openings over 3 years relative to existing businesses
15%	Survival, a low closure rate over 3 years
10%	Financial trend, gross profit growth of companies filing accounts in the municipality

A part that can't be calculated for an area is left out and the other parts count proportionally more – for example momentum and survival while closures are known for less than three years (Norway, Sweden). Countries and regions get no score, as there are no similar-sized areas to compare them with.

Each part is a percentile among comparable areas. In small areas, where only a few businesses are expected, the “room in the market” part is pulled toward neutral, and results are marked low confidence.

Good to know

• Some businesses register at a home or accountant's address rather than where they work, especially trades. Use the radius view for them.
• A low number can mean opportunity, or low demand. Always look at the trend, the comparable areas and the local situation.
• Parish (sogn) figures are the closest thing to “neighbourhoods” in official statistics.