Data, analytics & business intelligence
One version of the numbers, refreshed automatically, that nobody has to rebuild in Excel on the last Friday of the month.
We build the data layer between your operational systems and your decisions: pipelines that extract and consolidate data from CRM, finance, web and operational systems; a warehouse or semantic model with agreed definitions; and Power BI dashboards on top.
The common starting point is a reporting pack that takes someone two days a month to assemble by hand, with numbers that disagree between departments. We replace it with a governed, scheduled pipeline and a single agreed definition of each metric.
What this covers
- Data warehouse and semantic model design
- ETL and ELT pipeline engineering
- Power BI dashboards and reporting
- Reporting automation
- Data quality and governance
- SQL Server performance tuning
What we deliver
Warehouse & modelling
Dimensional or lakehouse modelling in Azure SQL, Synapse or Fabric, with a documented semantic layer so 'revenue' means one thing across the business.
Pipelines & integration
Azure Data Factory, Fabric pipelines or custom .NET services pulling from CRM, finance, e-commerce, web analytics and operational databases on a schedule you can rely on.
Dashboards & reporting
Power BI built around decisions rather than every available chart — with row-level security so people see their own numbers and nobody else's.
Reporting automation
Scheduled distribution, alert thresholds and exception reporting, so the month-end pack assembles itself and someone gets told when a number moves.
Data quality & governance
Validation rules, reconciliation checks, lineage documentation and a defined owner per dataset. Trust in reporting is destroyed once and rebuilt slowly.
Database performance
Index and query tuning, execution plan analysis, partitioning and archiving on SQL Server and Azure SQL estates that have grown past their original design.
Often combined with
CRM & Business Systems
CRM only pays for itself when it is connected to everything else. We do the implementation and, more importantly, the …
ExploreCloud & DevOps
Infrastructure you can reason about, deployments that are boring, and a monthly cloud bill that reflects what you actu…
ExploreWeb Application Development
Not brochure websites. Software that runs a process: customer portals, quoting and booking engines, internal operation…
ExploreFrequently asked questions
Do we need a data warehouse, or can we report straight from our systems?
If you report from one system and the volumes are modest, report directly — a warehouse is overhead you do not need. You need one when you must combine sources, when reporting queries are slowing your production database, when you need history your source system overwrites, or when different teams derive different answers from the same question.
Power BI, Tableau or Looker?
For UK organisations already on Microsoft 365, Power BI is almost always the right answer: licensing is cheap or already included, it integrates natively with Azure and Excel, and the skills are widely available. Tableau is stronger for exploratory visual analysis. Looker suits engineering-led teams wanting version-controlled modelling.
How long before we see something useful?
We aim for a first working dashboard on real data within 3 to 4 weeks, deliberately narrow — one domain, a handful of agreed metrics. Broad programmes that surface nothing for six months are how data projects lose their sponsor.
Our data is a mess. Is that a blocker?
No, it is the normal starting position and part of the work. What matters is agreeing definitions and owners early. The technical cleansing is straightforward; deciding whose definition of an 'active customer' wins is the part that needs your input.
Can you report on data from our mobile app and website?
Yes. We instrument applications with a defined event taxonomy — rather than whatever the previous developer happened to log — and pipe GA4, app analytics and back-end events into the same model as your commercial data, so acquisition and revenue can finally be compared.
Talk to an engineer, not an account manager
Send us the problem and we will tell you honestly whether we are the right team, what a sensible first step is, and roughly what it costs.