Power BI & Microsoft Fabric
Semantic modelling, DAX, row-level security, deployment pipelines, lakehouse and warehouse integration. The deepest bench we have.
SERVICE
Dashboards leadership actually trusts.
Build, migration and rescue work across Power BI, Tableau, BusinessObjects, Qlik, Cognos, Looker and SSRS — with the data model treated as the real deliverable.
PLATFORM AGNOSTIC
We work in the tool you have.
We are not a reseller and we do not get paid to move you anywhere. Some clients are consolidating onto one platform; some are staying put and want what they own to work properly. Both are fine.
Tableau
Workbook and data-source rationalisation, extract and live-connection strategy, Tableau Server and Cloud governance, published data sources.
SAP BusinessObjects
Universe design and repair, Web Intelligence, Crystal Reports, and migration paths off BO when the licence renewal forces the question.
Qlik, Cognos & Looker
Sense and QlikView applications, Cognos Analytics and Framework Manager, LookML models. Migration in either direction, honestly assessed.
SSRS & paginated reporting
The operational reports nobody talks about but finance cannot close without. Modernised or kept running, whichever is cheaper.
Cross-platform migration
Any of the above to any other. The hard part is never the visuals — it is the undocumented logic underneath them.
THE PROBLEM
Three ways this usually goes wrong.
The lift-and-shift. Every workbook is rebuilt one-to-one in the new platform. Nothing is rationalised. You now pay less in licensing and have the same reporting mess, plus a change-management problem.
The dashboard-first build. Visuals get built against a flat extract because it is quicker. Six months later refresh times are unacceptable, measures disagree with each other, and nobody can explain why.
The AI disappointment. Copilot, Tableau Pulse or whichever natural-language layer gets switched on and immediately answers questions wrongly, because the model has ambiguous names, missing relationships and no documented measure definitions. The tool gets blamed.
WHAT WE DO INSTEAD
- Rationalise first. Usage telemetry tells us which of your reports are actually opened. Typically a large share are not, and rebuilding them is waste.
- Model properly. Star schema, conformed dimensions, one definition per measure, logic that is readable a year later — whether that is DAX, a Tableau data source, a BO universe or LookML.
- Prepare for AI. Descriptions, synonyms, verified answers and sample questions maintained as source-controlled metadata, so the natural-language layer resolves against a model that is legible to it.
- Govern from the start. Workspaces, projects, deployment pipelines, row-level security and a naming standard before there are two hundred reports to retrofit.
- Reconcile before cutover. Parallel run against the outgoing platform, with differences explained rather than averaged away.
WHERE AI GENUINELY HELPS
Used carefully, it takes real work off the table.
We are not going to tell you AI replaces a BI team. It does compress specific, tedious parts of the job — and we use it on our own delivery, which is part of why our estimates are shorter than they used to be.
Model assistance
AI assistants can propose relationships, rename inconsistent columns and draft calculations against an existing model. We review every suggestion; nothing ships unreviewed.
Natural-language answers
Once metadata is prepared properly, business users can ask questions in plain English and get an answer that traces back to a governed measure rather than an improvised calculation.
Migration acceleration
Parsing legacy workbook definitions, extracting calculation logic and drafting equivalents is well suited to automation. Validation is not, and stays manual.
Documentation that survives
Measure descriptions, lineage notes and data dictionaries generated as part of delivery rather than promised and never written.
Anomaly and driver analysis
Key influencers, decomposition and narrative summaries built into the reports so the obvious follow-up question is already answered on the page.
Agent-ready assets
Agent tooling can read and act on well-formed models. Building to that standard now avoids a rebuild when you want it later.
ENGAGEMENT SHAPES
Four ways to start.
We do not publish rates, because the honest answer depends on estate size, source-system condition and how much of the work your team wants to keep. You will get a fixed number after the first call, not a range that moves later.
ASSESSMENT
Estate review
Two to three weeks. Inventory of what exists, what is used, what should be retired, and what a migration would actually involve. You get a written findings document and a costed plan.
Right when: you suspect you are paying for more BI than you use, or a migration has been proposed and you want a second opinion before committing.
MIGRATION
Platform move
Between any two of Power BI, Tableau, BusinessObjects, Qlik, Cognos, Looker or SSRS. Rationalise, remodel, rebuild, reconcile, cut over. Phased by business area so nothing goes dark.
Right when: a licence renewal is forcing a decision, or you are paying for two platforms that do the same job.
BUILD
New implementation
Greenfield on whichever platform fits. Source integration, warehouse or lakehouse, data model, dashboards, security and governance — set up so it is still maintainable at report number two hundred.
Right when: reporting currently means spreadsheets emailed on Monday morning, and you want to stop that permanently.
RESCUE & RUN
Fix and maintain
An existing estate that is slow, contradictory or untrusted. We diagnose, remediate and can stay on retainer for enhancement and support afterwards.
Right when: you have the tool already and leadership has quietly gone back to exporting to Excel.
COMMON QUESTIONS
Asked and answered.
Which platform should we be on?
It depends far more on what you already own than on any feature comparison. If you are on Microsoft 365 E5, Power BI is often effectively bundled and the maths is hard to argue with. If you have deep Tableau skills in-house and renewal is not painful, moving may destroy more value than it creates. We will model it with your actual seat counts rather than quote a vendor case study.
How long does a migration take?
It depends almost entirely on how many reports survive rationalisation. A departmental move is usually weeks; a multi-thousand-workbook enterprise estate is a phased programme measured in quarters. The estate review exists precisely so you get a real number before committing.
Will this cut our licensing cost?
Often substantially — Power BI Pro is around fourteen dollars per user per month against roughly seventy-five for a Tableau Creator seat. But the saving is real only after you subtract migration cost and the internal time it consumes. We will show you that arithmetic honestly, including when it does not favour moving.
Can the AI just build our dashboards?
It can accelerate parts of the work meaningfully, and it is genuinely useful against a well-formed model. It cannot decide what your business means by 'active customer', and it will answer confidently even when your model is ambiguous. The preparation is the job.
What happens to our existing team?
They stay, and ideally they end up doing more interesting work. Every engagement includes handover; if you want us gone in six months, that is a reasonable and achievable goal to set at the start.
Can you supply people rather than run the project?
Yes. If you want a senior BI consultant embedded in your team rather than a delivery engagement, that is a staffing conversation and we can do that instead.
Bring us the estate you are worried about.
We will tell you what it would take, in writing, before you commit to anything. Or email sales@prodigym.org directly.