Enter a world of data with our data lake
Our data lake counts more than 800 variables; sourced from national registers, statistical bureaux, behavioural & opinion bureaux, along with a suite of predictive models and segmentation models that we have developed. In our data catalogues you get a detailed understanding and overview of our most often requested variables
To grant you the highest data quality, all data in our data lake come from reliable sources; public, national registers, either 1-to-1 or as statistical variables. We structure, validate, and update them continuously; whilst also growing the data components by adding new sources. Furthermore,our team of data experts can guide you to the right data for your organisation, the most relevant segmentation variables for your project, and the nature and structure of the register data
With flexible access points, all this makes it easy for you to implement data into your data science and business processes; it's just plug & play!
Data overview
Demographic data
Optimised statistical clusters
Denmark, Finland, Norway, Sweden
Common variables
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- Family type
- Life-phase
- No. children
- Education level
- Employment status
- Car ownership
- Age
- Etc.
Economic variables
Optimised statistical clusters
Denmark, Finland, Norway, Sweden
Common variables
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- Income- personal & household
- Wealth
- Etc.
Address data
1:1 address database
Denmark, Finland, Norway, Sweden
Common variables
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- Number, street, post code, region, X/Y co-ordinates
- Cluster grids
- Drive-time data
- Etc.
Prospect universe data
1:1 from open telephone registers
Denmark, Finland, Norway, Sweden
Common variables
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- Full name
- Telephone Mobile
- Telephone Landline
- Decision Maker (18+) = Woman
- Decision Maker (18+) = Man
- Validated contact details
- Etc.
Modelled data
Statistical models
Denmark, Finland, Norway, Sweden
Common variables
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- conzoom®
- Share-of-Wallet
- Propensity to buy
- Attitude to money
- RFM
- Opinion / Behavioural (e.g. Kantar based, or digital based etc.)
- Etc.
Company data
1:1 company register
Denmark, Norway, Sweden
Common variables
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- Contact details
- Industry
- No. employees
- Financials
- Etc.
Opinion level data
Qualitative survey data
Denmark, Norway, Sweden
Common variables
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- Access to TNS Kantar survey database, plus othher panel databases (e.g. Wilke)
- Full survey level data linked via respondance address & conzoom®type
- Etc.
Property data
1:1 property register
Denmark
Common variables
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- Size
- Building age
- No. bathrooms
- Heating type
- Etc.
Data catalogues
Our data catalogues display the most sought-after variable in our data lake from each of the Nordic countries: Denmark, Finland, Norway, and Sweden. However, if you do not find what you are looking for, do not hesitate to reach out as we work with or have in-depth knowledge of a number of additional registers as well
Our SME says
Data lake vs data warehouse
A data lake differs from a data warehouse by enabling you to operationalise both structured and unstructured data. Unlike a data warehouse that has a predefined purpose for working with structured and filtered data – usually to support reporting capabilities; a data-lake is much more fluid in nature and allows you to collate data from all different areas and sources across your business; your CRM, transactional data, customer satisfaction surveys, omni-channel marketing data; customer interactions etc. and work with them without the need for pre-determined structure
Our data lake gives you easy access to add more than 800 3rd party variables to the mix – data that has a wide variety of business benefits and customer insights, is GDPR compliant and agile: ideal for implementing in machine learning and predictive analytics