Dashboards are the part the business sees; the platform underneath is what makes the numbers hold. We build both — so the board reads one number, and every figure ties back to its source.
Finance has one revenue figure, sales another, the board pack a third — and month-end becomes an argument about whose spreadsheet is right. Every new dashboard adds speed to the chaos, not clarity: more extracts, more definitions, more numbers that almost match.
The problem is rarely the reporting tool. It's that there is no single, governed place where the business agrees what its numbers mean.
We put one governed data platform under the whole business — sources reconciled, metrics defined once, access controlled — and build the reporting on top of it. Finance, ops and the board read the same number, and every figure walks back to its source.
The same platform carries reporting today, and data science and AI tomorrow — one foundation instead of three systems feeding each other.
Decisions made off one set of numbers. Less time in spreadsheet-vs-spreadsheet arguments. Faster month-end. Reporting that stands up to auditor and regulator without a scramble — on one platform that carries reporting, data science and tomorrow's AI side by side, instead of three systems feeding each other.
Early to mid maturity. Useful from the first dashboard onward. Bigger payoff once the whole group works from one definition of every metric.
Where this lands in practice. Each row opens with the detail — and what it buys you.
Single definition of revenue, customer, asset, event — across brands, subsidiaries and source systems.
The payoff. Meetings start at “what do we do about it” instead of “whose number is right”.
Auditable monthly packs, daily refresh on critical numbers, exception highlighting. Numbers that hold up.
The payoff. Board packs that survive the hardest question in the room.
Live views for the people running the day — stock, queues, sales, incidents — interactive enough to answer the follow-up question without a ticket to BI.
The payoff. Decisions made this hour, on numbers from this hour.
Curated datasets, governed measures, training pathways. Lets analysts build without breaking the model.
The payoff. The BI team stops being a bottleneck without losing control of the numbers.
Customer-facing analytics inside SaaS products, with row-level security and multi-tenant isolation.
The payoff. Your data stops being a cost centre and starts being a feature.
Who owns each metric, what it means, who may see it, and how quality is enforced — the rules that make every number defensible, without slowing the teams who use it.
The payoff. Every number defensible; no governance theatre.
Bronze / Silver / Gold layers, governance baked in, semantic layer on top. The auditor can walk a Gold figure back to a Bronze event.
The payoff. The auditor walks a Gold figure back to a Bronze event — and stops asking.
Shared infrastructure, tenant-specific transformations, group-level governance. Reusable across portfolio companies.
The payoff. One platform investment paying off across the whole portfolio.
Event-level data for audience, sensor, transaction and fraud-style use cases. Backpressure-aware, replayable.
The payoff. The business reacts while the event still matters.
Reports and models moved from Tableau, SSRS and SSAS onto Power BI — logic preserved, definitions carried into the governed model, and users landing on one platform instead of three.
The payoff. Three licence bills and three versions of the truth become one.
Through the Moberg Delivery Framework — the same five stages, governance and engineering standards we run on every engagement, from business case to long-term run. Microsoft and Databricks have both independently validated this practice — but the measure that matters is one number nobody argues with.