Data & Analytics
Decisions backed by numbers — and by a data platform your team can trust.
Most data problems are not modelling problems; they are ownership problems. A dashboard nobody owns does not stay right. A pipeline with no contract becomes a hand-grenade on someone else's deploy. We build warehouses, pipelines, and dashboards with explicit ownership, explicit tests, and an explicit answer to 'what question does this table exist to answer?'.
Offerings in this practice
Data warehouse design
Dimensional, lakehouse, or a pragmatic mix. We start with the three questions the business is actually trying to answer, then design the model backwards from there.
Pipelines & ingestion
Reliable, idempotent, rerunnable pipelines on Airflow, Dagster, or native cloud schedulers. Data contracts between producers and consumers, not hopeful JSON.
Analytics & BI
Executive dashboards that end arguments. Semantic layers so finance, product, and ops use the same definition of "active customer".
Machine learning delivery
Model training, deployment, and monitoring — not prototype notebooks. Feature stores, evaluation infrastructure, drift detection, and clear ownership.
What "done" looks like.
- 01 One definition of every key metric, shared across the business.
- 02 Pipelines that are monitored, rerunnable, and owned by a named team.
- 03 Dashboards your leadership actually uses in meetings — because they trust them.
- 04 A hand-over runbook your analytics engineers can run the day after we leave.
Is your data stack working for you — or consuming you?
A short paid audit will tell you which. We read the code, interview the analysts, and write it up in plain English.