Engineered capability
Business Intelligence
Decision-grade business intelligence engineered into executive workflows — metrics, KPIs, and operational visibility at the cadence the board actually meets.
02 — Engineering practice
How we engineer it.
Business intelligence fails when it is treated as reporting. It succeeds when it is engineered as decision infrastructure — the set of metrics, dimensions, and views the operating model is actually steered by, delivered at the cadence executive decisions are actually made.
Our practice begins with the decision map: which decisions does the executive team make, against which metrics, on which cadence, under which thresholds. From there we engineer the metric layer — single-sourced, governed, versioned — and the reporting surface that delivers those metrics with the precision and context required.
We instrument the decision surface itself. Which metrics are consulted, by whom, before which decisions — because the business intelligence that compounds is the business intelligence that is actually used. Dashboards that are not used are not intelligence; they are technical debt.
03 — Engineering surface
The technologies behind this capability.
A selection of the platforms, frameworks, and tools our principals engineer with in production engagements.
Semantic & Metric Layer
- dbt Semantic Layer
- Cube
- LookML
- MetricFlow
BI & Visualization
- Looker
- Power BI
- Tableau
- Metabase
- Superset
Operational Surface
- Slack / Teams alerts
- Embedded analytics
- Snowflake
- BigQuery
- PostgreSQL
Engage on this capability
Scope this capability against your operating model.
Briefings are scoped within five working days and led by a senior architect.
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