A real data model behind your dashboards
We design and build the data model your analytics relies on: entities, relationships, fact grain, dimensions and reporting datasets. No duplicated logic or conflicting KPIs.
What’s included
We build the model from business questions, not raw tables.
Business mapped into data
Identify core entities: users, orders, campaigns, products, transactions.
Conceptual model
Define how entities relate and which business questions analytics must answer.
Logical model & schema
Design tables, keys, fact grain, dimensions. Choose architecture: star / snowflake / vault.
BI-ready data layer
Build marts/views for Power BI / Looker so metrics are calculated consistently everywhere.
What a proper data model gives you
Single source of truth
One structure, one logic, one answer to every KPI question.
Stable dashboards
Reports don’t break when new data sources or metrics appear.
Transparent unit economics
LTV, CAC, ROI and other KPIs are calculated the same way across products and channels.
Scales without pain
The model grows with your business instead of collapsing under complexity.
Why data modeling comes first
Business logic becomes explicit
As long as logic exists only in people’s heads, analytics will stay unstable.
Reports stop contradicting each other
Because everyone uses the same data model, not separate spreadsheets.
ETL becomes easier
With a clear model, engineers build pipelines faster and without chaos.
Typical problems solved by a data model
Need a proper data model?
Describe your business and analytics tasks. We’ll propose a concrete data modeling plan.