Solutions
Data & analytics
One model of your business, defined once, that reports, dashboards and predictions all read from — so two teams stop disagreeing about the same number.
Three dashboards, three answers
When every report defines "active customer" for itself, the definitions drift and the meetings become arguments about whose number is right. The fix is not another dashboard. It is one place the definition lives.
What we do
A modelled layer, not extracts
Tables, the joins between them, filters and formula columns — kept as a dataset rather than rebuilt per question.
Cubes when live queries stop being viable
When a source table gets too big to query directly, the same picker turns it into a pre-aggregated copy at a grain you choose, costed before it is built.
Reports and dashboards on top of that model
Dashboards are built on saved reports, and reports on the model. Nothing recomputes from raw tables at any layer.
Prediction on the same model
Pick an objective, see the features it needs, map what you already have, fill the gaps, then train. Features derived for a prediction come back into reports.
How an engagement runs
- 1Connect
Point at the databases you already have — Postgres, MySQL and SQL Server, plus CSV and Excel imports.
- 2Model
Agree the definitions once, in the dataset layer.
- 3Build
The reports and dashboards people actually asked for.
- 4Predict
Where there is enough history to justify it, and not before.
What it is built on
Delivered on the analytics half of the Pro Suite, with the chart and table packages published openly.
See it against your own data
A demo runs on your schema, not a sample dataset. Thirty minutes, no deck.