C.2 · Data Engineering & Analytics
Business Intelligence & Reporting
One definition of a metric, consumed by every tool downstream
What we build
Reporting that a leadership team can actually argue from. A semantic layer holding metric and dimension definitions in one place, dashboards designed for a decision rather than for a screenshot, self-service models that do not require a data team for every question, scheduled and event-driven distribution, and a certification process so people know which report is authoritative.
Capabilities
- A semantic layer where each metric is defined once and consumed everywhere
- Dashboards designed around the decision, not around the available chart types
- Self-service models scoped so a business user cannot accidentally build a wrong number
- Certified and uncertified content clearly separated, so authority is visible
- Scheduled, embedded, and event-driven distribution to the people who act on it
- Usage analytics on the reports themselves, so dead dashboards get retired
Related services
How it connects
Where it sits in the stack.
This service, and the two it hands off to. None of them can be optimised alone.
Business Intelligence
Reporting that a leadership team can actually argue from.
Data Platforms
Data platforms built for freshness and lineage.
Data Engineering & Analytics · see serviceIntegration & Migration
Pipelines and migrations that can be verified rather than trusted.
Data Engineering & Analytics · see serviceBring us the whole problem.
Tell us where the work is stuck, whether that is a model that never reached production, an application nobody can change, a data platform nobody trusts, or a plant the business cannot see. An engineer replies with a first read, not a sales deck.