BI Dashboards
Decision surfaces with a clear owner, a defined question and a review cadence. We retire the reports nobody opens.
Talk this throughAnalytics
Dashboards people open, numbers people agree on
Most BI fails on definitions, not visuals. We fix the metric layer first, then build the decision surfaces on top of it.
MWRKJT
Delivery leads online — talk to a human, not a bot1Definition per metric
ExecDashboards leaders trust
Real-timeWhere it matters
Decision surfaceMetrics · trend · drivers
100% delivery success — delivered worldwide across seven regions
AWS
Microsoft Azure
Google Cloud
Databricks
Snowflake
dbt
Power BI
Looker Studio
Azure Synapse
MongoDB
Python
LangChain
AWS
Microsoft Azure
Google Cloud
Databricks
Snowflake
dbt
Power BI
Looker Studio
Azure Synapse
MongoDB
Python
LangChain
What you get
A dashboard is only as good as the metric behind it
When finance, sales and operations each calculate revenue differently, no chart will save you. We agree the definitions, encode them once in a semantic layer, and build from there.
- A metric catalogue with owners, definitions and change history
- Semantic layer enforced in code so every tool reads the same logic
- Dashboards designed around a decision, not around available fields
- Row-level security that mirrors your org, tested before launch
- Adoption tracked — we look at who actually opens it
Trend and horizonActuals vs forecast band
Capabilities
Analytics that reaches the business
Built in Power BI, Looker, Fabric or your existing tool.
Customer Analytics
Cohorts, retention curves, churn drivers and behavioural segments, wired into the systems your teams already work in.
Talk this throughEmbedded Analytics
Reporting inside your own product, multi-tenant and permission-aware — often a revenue line rather than a cost line.
Talk this throughMarketing Analytics
Spend, attribution and efficiency measured against booked revenue instead of platform-reported conversions.
Talk this throughRevenue Analytics
Pipeline health, pricing realisation and margin by product, channel and cohort, reconciled to the ledger.
Talk this throughBy the numbers
Analytics in numbers
Grounded in real analytics and BI work — from Looker Studio to Power BI — on named engagements.
0+EMEA countries reporting on one platform
0%Manual reporting workload removed
0Agreed definition per metric, enforced in code
0%Figures traceable to a governed source
Delivery model
How the work actually runs
One delivery model, whatever the engagement. You always know what is shipping this week and what it is worth.
01
Discovery
We map your sources, decisions and blockers, understand the business goal, and agree what success looks like before anything is built.
02
Solution design
We design the architecture, data models and use cases — right-sized to your team and your cloud — and cost the work before you commit.
03
Development
Weekly sprints against a visible backlog: pipelines, models, dashboards and applications, all in version control and yours from day one.
04
Testing & validation
Every pipeline and model is tested — with frameworks like PyTest and Great Expectations — so the numbers are trustworthy before they ship.
05
Deployment & training
We deploy into your cloud and train the people who will run it, so the capability lands with your team, not just our code.
06
Support & optimisation
Observability, alerting and continuous improvement keep the system fast, accurate and cost-efficient long after go-live.
Proof
Recent work
Marketing · EMEA
Marketing and CRM data unified across 20+ EMEA countries
A digital-transformation programme that consolidated marketing and CRM data across the region on Azure and Power BI, with a custom lead-management automation built on Power & Logic Apps.
80%Manual workload cut
20+EMEA countries
FMCG · Nestlé
Workforce analytics for Nestlé’s supply & demand planning
HR data marts on SAP feeding automated daily ingestions through AWS Glue and Databricks, on a medallion architecture, so planners could see available resource against production targets.
DailyAutomated ingestions
MedallionData architecture
Data strategy · Germany
One source of truth from 50+ scattered sources
Data strategy and cloud architecture on Google Cloud, ingesting 50+ sources through Stitch, modelled in dbt and surfaced to the CEO and Head of Product in Looker Studio.
50+Sources unified
ExecLive dashboards
FAQ
Questions buyers actually ask
Straight answers. If yours is not here, ask us on a call — we will tell you if we are the wrong fit.
Ask a questionNo. In most cases we keep the tool and rebuild what sits underneath it. Tool migrations are the last resort, not the opening move.
Every dashboard gets an owner, a question it answers and a review date. Anything unopened for a quarter goes to an archive. It is a governance habit more than a technology.
Yes — embedded, multi-tenant reporting with permissions inherited from your application. It is one of the few analytics investments that shows up directly in revenue.
Your team. We document the model layer, train the analysts and leave the definitions in version control where they can be reviewed like any other code.
Next step
Ready to find out what your data is worth?
Thirty minutes with a delivery lead, not a salesperson. You leave with a point of view on your highest-value use case and what it takes to ship it.