Danish data

Our Nordic data lake counts 800+ 3rd party variables including statistical data and data from official registers. Here we have grouped the most frequently requested Danish variables

Our Danish data lake contains data on

ZAP

DAR

Map

Authority record

Distance

Drive time

Flood

Climate

Energy class

Energy usage

Conservation data

OIS

Registration

Tender data

Habitation zone

Name & phone number

Family type

Marital status

Income & wealth

Occupation level

Education

Car ownership

Relationships

Gazette

CVR annual

CVR master data

Movement analysis

Geo data

Historical trends

... and much more!

 

Explore the variables in our data catalogues

Our Danish data catalogues display the most frequently demanded variables for marketing and analysis & modelling in our Nordic data lake. To offer you the best data quality, we  only use data from national registers, either as 1-to-1 data or statistical variables. We validate the data before it is added to our data lake, and our team of data specialists can guide you to the right data for your organisation as well as on the registers' structure. If you are looking for a variable not presented in the data catalogues, do not hesitate to get in touch with us as we have in-depth expertise of many more variables and register data

Data for marketing

Data for analysis & modelling

Our machine learning tool Predict blend your customer data with our 3rd party variables and rank them due to their importance for your analysis

We can help you identify the relevant data

Data-driven decisions are important for efficiency and precision but identifying the right data to use can be a lot of work. With our Predict report we make it easy for you to identify the most explanatory variables when you want to analyse your customers' churn, cross-sell potential or life-time value. We do so with our machine learning tools, developed to blend your internal customers data with all the data in our data lake. The result is a Predict report showing you the most important variables for your analysis, across your own data and our 3rd party data

 

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