A data warehouse can retrieve large amounts of data from several different data sources such as CRM (Salesforce, SAP, Hubspot, Upsales, Pipedrive, etc.), marketing platforms (Meta, LinkedIn, Google, Mailchimp, etc.) and sales platforms (Shopify, Klarna, etc.). We make the process modular, automated for the collection, storage and analysis of mixed data sources.

The difference between a data warehouse and a data lake:

A data warehouse is typically used for structured data and business intelligence, while a data lake is more suited for storing and processing raw data for a wide variety of use cases.


By building a data warehouse, we automate away repetitive tasks and streamline your processes. Data storage is necessary when handling large amounts of data and a core component for developing your business intelligence.


  • Kickoff meeting where we map out all your data sources (e.g marketing channels, CRM-system, financial system, etc.)
  • We provide a suggestion of a complete solution for your data layer, based on your existing systems. 
  • Together we decide on a data warehouse. 
  • We set up data storage and create all accounts and regulations for those who will work with in it.
  • Feedback
  • Delivery and hand-over

Self evaluation

  • Do you need to compare different data sources with each other and over different time periods?
  • Is the data difficult to analyze and does not reflect the terminology within your business?
  • Do you want to eliminate repetitative tasks? 
  • Do you need to make all data available for better decision-making in the organization? 

If yes on any of the questions above, then this step is best suited for you!

Want to know more?

If you have any questions or want to know more about how we work, we are more than happy to help. Send us an email, call us, or send as a dove and we will get back to you asap! 🕊️✌️