Services / Microsoft & BI
Power BI & Analytics
Dashboards fail for one of two reasons: nobody agrees what a number means, or nobody trusts where it came from. We build the semantic model and the definitions before the visuals, so a single metric has a single answer everywhere it appears.
- Practice
- Microsoft & BI
- Best fit
- Best fit once transactional data lives in an ERP or CRM and the reporting burden has moved into spreadsheets.
- Industries
- Manufacturing · Distribution · Retail · Textile · Healthcare · Professional Services
What’s included
Scope, stated before we start
Six work-streams that make up a standard engagement. Anything outside them is priced separately and named in the proposal — never absorbed quietly.
Semantic model & metric dictionary
A star-schema model with documented DAX measures and a written definition for every metric — gross margin, on-time delivery, DSO — signed off by the people who argue about them.
Data pipeline & refresh
Dataflows or Fabric pipelines from ERP, CRM and operational sources, with incremental refresh, gateway configuration and failure alerting.
Executive & operational reports
A short executive pack designed for decisions, plus operational reports at the grain the team works in. Different audiences, one model.
Row-level security & workspaces
RLS by entity, branch or sales territory, workspace and app lifecycle across dev/test/prod, and a deployment pipeline instead of file emails.
Performance tuning
Model size reduction, aggregation tables, query-fold auditing and visual-level optimisation so a page renders in under two seconds on the real dataset.
Analyst enablement
We train your analysts on the model we built, hand over the documentation, and stay available for review — the goal is that you stop needing us.
Outcomes
What changes when this is done properly
These are the three differences clients describe six months after go-live — not feature claims.
- One definition per metric, documented
- Month-end reporting cut to days
- Reports that load fast enough to be used daily
Not sure this is the right service? Discover is a fixed-price, two-to-three week assessment that answers the question with evidence — and it is usable whether or not you appoint us. Start there instead →
Who it’s for
Industries where this comes up most
Each links to how the service is shaped for that sector — the requirements differ more than vendors admit.
Our approach
The same four phases, applied to this scope
Reused deliberately. A consistent method is what makes a fixed price honest and a date holdable.
01
Discover
Process mapping before software selection.
We walk the floor and the ledger. Two to three weeks of structured interviews and document tracing produce a current-state process map, a data-quality baseline, and a written list of the decisions your systems cannot currently answer.
02
Design
One target architecture, agreed on paper.
Chart of accounts, item and customer master rules, approval hierarchies, integration contracts and reporting model are designed together — not discovered during build. You sign off a blueprint, not a demo.
03
Deliver
Configure, migrate, test, train — in that order.
Iterative configuration with fortnightly conference-room pilots. Data migration runs three times before go-live: trial, dry run, and cutover, each reconciled to the closing trial balance. Users train on their own data.
04
Sustain
Hypercare, then measurable adoption.
Four to eight weeks of hypercare with named owners and a burn-down of issues. Then a governance rhythm: master-data stewardship, monthly close review, and a Power BI adoption dashboard that shows whether the system is actually being used.
Related case study
Product costing the shop floor actually recognises
Standard costs that had drifted for years rebuilt against real routings and consumption, with shop-floor capture on rugged terminals and variance reported per production order.
Our board finally reads the same numbers we do. Month-end reporting dropped from eleven working days to four, and nobody rebuilds a spreadsheet to get there.
Yes, but rarely straight to production tables. We put a governed view or warehouse layer in between so reporting load never competes with transaction processing and model logic survives an ERP upgrade.
Not to start. Pro or Premium Per User covers most mid-market needs. Fabric earns its place when you need a lakehouse, large-scale refresh or data-science workloads — we will tell you when you cross that line rather than sell it upfront.
Your analysts, with our documentation and a monthly review if you want it. Every measure is commented and every source documented so the model does not depend on one person.
We surface the conflict early and force a decision in a definitions workshop. The disagreement is the deliverable; the dashboard just reflects the resolution.
Next step
Talk to someone who has implemented Power BI before
Not a sales call. A working conversation with the person who would run the engagement, and a straight answer on scope, sequence and cost.