A data foundation built on the entities your business actually has.
Domain modelling and warehouse architecture designed to survive growth, tool changes, and new use cases.
When the data sprawl catches up
You have data in HubSpot, Stripe, your product database, three spreadsheets, and a tool nobody remembers buying. Reports contradict each other. New questions take weeks to answer. Trust is eroding.
You know the foundations are wrong but rebuilding feels like a year-long expedition with no clear payoff.
We design domain models and warehouse architectures for B2B businesses — usually deployed on Snowflake or BigQuery with dbt for transformations.
How we architect
- 01
Domain model
Entities, events, metrics defined before any pipeline is written.
- 02
Warehouse design
Schemas, naming conventions, layering (raw / staged / marts) — designed to scale.
- 03
Migrate or build
Move existing pipelines onto the new architecture incrementally; build new ones to the standard.
What good looks like
New questions can be answered in days, not weeks. New tools plug into the existing model. The same number means the same thing across every dashboard.
Single source of truth
Every team queries the same defined metrics.
Composable stack
Add or swap tools without rebuilding.
Future-proof
New use cases extend the model rather than fork it.
Proof
70% faster time-to-answer
Domain-first architecture cut time-to-answer for ad-hoc business questions from 2 weeks to 2 days.
— B2B SaaS analytics team
Frequently asked questions
8–14 weeks for the model and core architecture. Migrations of existing pipelines run in parallel and finish over 3–6 months.
Ready to fix the foundations?
A 60-minute call to map your current stack and the three things we would change first.