Decisions that run on evidence
Pipelines, warehouses and dashboards, data collected once, trusted everywhere, and turned into surfaces people actually use to decide.
Strategy, design and engineering, one practice, delivered in slices.
One number, one truth, one place.
The practice.
Most organisations don't lack data, they lack trust in it. Numbers disagree between meetings, reports are assembled by hand each cycle, and the interesting signals sit locked in operational corners nobody queries. The fix is unglamorous and valuable: pipelines that reliably collect, models that define metrics once, and surfaces that answer questions in seconds.
We build that backbone and the decision layers above it. Warehouses modelled around your business rather than a generic template, fed by tested pipelines, surfaced in dashboards tuned to each audience: executive, operational, analytical. Definitions live in one place, lineage is traceable, and the quarter's arguments about whose number is right end.
Delivered as
- Fixed-scope projects
- Staged programmes
- Retainer partnerships
The workbench.
Included
Data pipelines
Collection and transformation flows, tested, monitored and recoverable, from sources to warehouse.
How the work runs.
Map
Sources, consumers and current pain mapped; the metric definitions that matter agreed.
Model
Warehouse and semantics designed, one definition per metric, lineage documented.
Build
Pipelines, tests and dashboards delivered iteratively with your team in the loop.
Institutionalise
Alerts on data quality, training for users and a rhythm of refinement as questions mature.
The kit
- PostgreSQL
- dbt
- Airflow
- Metabase
- Power BI
- Python
Asked about data.
The questions buyers raise before starting this kind of engagement, answered plainly.
A question we missed?With the decisions your business makes repeatedly. We map the few metric families that drive those decisions, build trust in them first, and expand outward, rather than boiling an ocean of dashboards nobody reads.
The one your team will open: Metabase or Looker Studio for lean teams, Power BI where the organisation already lives in Microsoft. We build on what sticks, and keep the semantic layer portable.
Yes, pipelines get tests, definitions get versioned, and quality alerts fire before the meeting where the number gets quoted. Trust is rebuilt one reliable cycle at a time.
No, this is the engineering that makes analysis trustworthy. Once foundations hold, forecasting and ML become possible; without them, every model inherits the mess.
Data & Analytics, frequently asked questions
Explore further.
One number, one truth, one flipchart.
the trend is up; the meeting is short.
Doodles from the studio, drawn the way we build, by hand
Need data & analytics that ships?
Tell us the problem and the constraints. We'll come back with an approach, a staged plan and an honest number, within days.