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