Service 01 · Data architecture
The blueprint before you build
Before cleaning, analysing or automating anything, someone has to decide where each piece of data lives, how it relates to the others, and where it's going to grow. That's data architecture: the map that makes everything else fit together.
The challenge
When data grows without a plan
Many companies store their data wherever the moment's need arises: a spreadsheet here, a standalone database there, a CRM that doesn't talk to billing. It works for a while — until you need to cross that information and no one really knows where each figure comes from, or every new hire takes weeks to understand how it all fits together. Data architecture is what prevents you from reaching that point, or what fixes it if you already have.
How we do it
Four steps, no shortcuts
Diagnosis
We map what data exists today, where it actually lives, and who uses it day to day.
Modelling
We design the schema — entities, relationships, flows — built for your real business, not a generic template.
Stack choice
We recommend where each piece of data should live: an operational database, a data warehouse, or both depending on the case.
Growth plan
We leave the architecture ready so adding a new source doesn't force you to redo everything.
Who it's for
- Growing companies whose data lives scattered across spreadsheets or standalone tools.
- Businesses launching a new product or area who want to start with a solid data foundation from day one.
- Teams that already have data, but no one dares touch the structure for fear of breaking something.
What you get
- A complete, documented architecture diagram.
- A data schema (entities, relationships, flows).
- A reasoned technology stack recommendation.
- A solid foundation to build cleaning, dashboards or AI agents on top of afterwards.
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