Data Engineering & Analytics
One version of the numbers, and the plumbing to keep it true.
Every AI and reporting project depends on data that is complete, current and defined the same way everywhere. We build the pipelines, models and dashboards that make that true, and document them so the next question takes hours rather than weeks.
Schedule 1
What is included
- B-4.1
Ingestion pipelines
Reliable, monitored extraction from SaaS tools, databases, files and APIs, with retries and alerting.
- B-4.2
Warehouse and modelling
A clean, tested data model in your warehouse, with metrics defined once and reused everywhere.
- B-4.3
Dashboards and self-serve BI
Dashboards built around decisions, plus a semantic layer so teams can answer their own questions safely.
- B-4.4
Data quality and governance
Tests, lineage, access control and retention rules, so the numbers can be trusted and audited.
Schedule 2
Typical projects
- A single source of truth for management reporting
- Preparing data for machine learning
- Replacing manual weekly spreadsheet reports
- Real-time operational dashboards
Materials
- PostgreSQL
- BigQuery
- Snowflake
- dbt
- Airflow
- Dagster
- DuckDB
- Metabase
- Power BI
Schedule 3
How it runs
- 01
Discovery · 1–2 weeks
We map the problem, the users, the data and the constraints, and agree what success will be measured by.
- 02
Blueprint · end of discovery
Architecture, scope, milestones and a fixed price for the first build phase, all in writing. You can stop here and keep the blueprint.
- 03
Build · weekly demos
Short iterations with a working demo each week, automated tests from day one and a shared board you can always see.
- 04
Launch & handover · planned cut-over
Staged rollout, monitoring switched on, documentation and a recorded handover session with your team.
- 05
Run & improve · optional
A monthly support plan, or nothing: the handover is written so that you never need us to keep the lights on.
Schedule 4
Common questions
Do we need a data warehouse?
Not always. For smaller volumes a well-modelled PostgreSQL database is enough. We recommend the smallest thing that answers your questions reliably.
Can you work with the BI tool we already use?
Yes. The modelling layer is tool-agnostic. Dashboards are built in whatever your team already logs into.