Data warehouse
Bring sales, finance, stock and operational data into one place — usually BigQuery — with a scheduled refresh.
One set of numbers, and everyone looking at it
Sales has one figure, finance has another, and the Monday report takes half a day to assemble. We pull your data into one place, agree what each number means, and build dashboards that update themselves.
3–4 weeks To a first dashboard running on live data
One source Every report reads from the same figures
Your accounts Warehouse and dashboards stay in your cloud
Capabilities
What this covers
Dashboards
Looker or Power BI dashboards built around the decisions people actually make, not every metric available.
Data pipelines
Pull from your databases, spreadsheets and SaaS tools automatically, and alert someone when a feed stops.
Agreed definitions
Write down what “revenue”, “active customer” and “margin” mean once, so every report uses the same figure.
Ask questions in plain English
Let people query the data in a sentence instead of waiting for someone to build a new report.
Forecasting
Demand, stock and revenue forecasts from your own history, with the uncertainty shown rather than hidden.
Deliverables
What you get at the end
Built so your team can run and extend it without us. That is what a good handover looks like.
- Data warehouse in your own cloud account
- Automated pipelines from each source system
- Dashboards for the teams that need them
- A written glossary of every metric and how it is calculated
- Documentation and handover for your team
Typical technology
Chosen per project against what you already run and what your team knows — never out of habit.
- BigQuery
- Looker
- Power BI
- Python
- Google Cloud
- AWS
How we choose technology
Ways to start
How to get started
Start small. A fixed-price first step gives both sides real information before anyone commits a build budget.
Data Review
We map where your data lives, what state it is in and which reports are worth building first.
First Dashboard
One area of the business — sales, stock or finance — brought together and live on real data.
Rollout
Further sources and teams added, with monitoring on every pipeline.
Do we need a data warehouse, or can we just connect Power BI to our systems?
For one or two sources, connecting directly is often fine and we will say so. Once you are joining several systems, or the reports slow your live database down, a warehouse is cheaper to run and far easier to trust.
Our data is a mess. Is that a problem?
It is normal. Part of the first week is finding out exactly how messy it is, and the fixes are built into the pipelines so the cleaning does not have to be repeated by hand.
Looker or Power BI?
If you already use Microsoft 365, Power BI usually fits best. If your data lives in Google Cloud, Looker does. We work in both and will recommend one based on what you already pay for.
How much does it cost to run?
For most small and mid-sized businesses the warehouse costs tens of pounds a month, plus dashboard licences. We show you the running cost before you commit.
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Describe what you are trying to achieve. You will speak to someone who does this work every week, and get a straight answer on fit, cost and timing.
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