Data & AI

One version of the truth,
and people actually using it

The problem is rarely missing data: it is five different figures for the same question and nobody knowing which one counts. We model, govern and deliver dashboards that get opened, not archived.

Power BIMicrosoft FabricDataverseDAXSQL Server
What we do

Five concrete things,
not a list of good intentions

Start with the data you already have

Before modelling anything: which sources exist, which ones contradict each other and who answers for each figure. It almost always turns out that two departments calculate the same thing differently, and that conversation is worth more than any dashboard.

A semantic model, not a loose report

One model with its measures, hierarchies and business rules written once. So when someone asks about margin, every dashboard gives the same answer — and adding the next report takes hours, not weeks.

Dashboards that answer questions

Not thirty charts just in case. Every page exists because someone has to make a decision with it, and it is designed for that decision.

Governance and automatic refresh

Certified sources, role-based permissions, scheduled refresh and alerts when something fails to load. A dashboard showing three-week-old data does more harm than no dashboard at all.

Advanced analytics when it earns its place

Demand forecasting, anomaly detection, segmentation. Only when the question calls for it: most decisions are answered well by descriptive data done properly.

What we use

The full stack,
no window dressing

Everything below is in real projects. If something isn't on the list, we tell you before we start and not after.

Visualisation and modelling

Power BI ServicePower BI DesktopPower BI EmbeddedMicrosoft FabricSemantic modelsDAXPower Query (M)Paginated Reports

Data and storage

Azure SQL DatabaseSQL ServerDataverseOneLakeAzure Data Lake StorageLakehouseWarehouseDelta ParquetCosmos DB

Integration and transformation

Data FactoryDataflows Gen2Azure SynapseNotebooksPySparkT-SQLPythonREST APIs

Advanced analytics

Azure Machine LearningPredictive analyticsDetección de anomalíasSeries temporalesCopilot en Power BI
Frequently asked

What everyone ends up asking

It depends on volume and whether you need ingestion and transformation at scale. For most mid-sized companies, Power BI with a well-built model solves 90 % at a fraction of the cost. Fabric earns its place when there are several large sources, a need for a lakehouse, or data teams working in parallel. We tell you in the assessment, and sometimes the answer is that you don't need it yet.

No. Excel is usually the most faithful record of how the business really works, exceptions and unwritten rules included. We read it, understand the rules inside and carry them into the model. What gets retired is Excel as the system of record, not the knowledge in it.

Three to five weeks for the first one with real data and automatic refresh. We don't hand over pretty mock-ups with invented numbers: they arrive faster and prove nothing.

Your team, because we build with them watching and hand over the model documented. If you'd rather we carry on, there is a support hour bank — but you won't depend on us out of ignorance.

Almost never at the start. Power BI Pro gets you a long way; Premium capacity earns its place with many read-only users, large models or very frequent refreshes. We give you the exact number before you buy anything.

Shall we talk about your case?

Twenty minutes is enough to know whether there's a project. If there isn't, we'll say so.