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Data & Analytics

Fewer reports, more answers

BI programmes that rationalise what exists, agree what the measures mean, and give analysts self-service without abandoning governance.

Data & Analytics

Business Intelligence Consulting

The typical mature BI estate has hundreds of reports, a small fraction of which are opened regularly, and several conflicting definitions of the measures executives care about most.

We rationalise from evidence — usage telemetry, not opinion — build one governed semantic layer, and rebuild the reports that survive on top of it. The result is a smaller estate people trust.

Platforms we typically deliver this on

Power BITableauDatabricksMicrosoft AzureSnowflake

All platforms and partners

What we do

Scope of the service

BI assessment and rationalisation

Usage analysis across the estate to identify what to keep, merge, rebuild or retire, with evidence for each call.

Semantic modelling

One governed definition per measure, exposed consistently to every consumption tool.

Dashboard design and build

Reports designed around the decision being made, tested with the people who will use them.

Self-service enablement

Certified datasets, workspace structure, naming standards and training so analysts build safely without a central queue.

Performance optimisation

Model and query tuning, aggregation and incremental refresh for datasets that have outgrown their design.

Migration between BI platforms

Assessment, logic translation and phased user migration between Power BI, Tableau and legacy tools.

Use cases

Where this is used

Representative engagements, described at the level our clients permit. Sector and shape are accurate; identifying detail is withheld.

Public sector

Reducing a 400-report estate

Usage telemetry showed under a fifth of reports were opened in a quarter. We rebuilt the essential set on a governed model and retired the rest with owner sign-off.

Outcome — A maintainable estate with agreed definitions behind every measure.

Healthcare

Operational dashboards for capacity management

Managers were assembling capacity views by hand each morning. We built operational dashboards refreshed intraday from the source systems.

Outcome — A morning routine replaced by a view that is already current.

Higher education

Self-service for institutional research

Every analytical question went through a small central team, creating a queue measured in weeks. Certified datasets and training moved routine analysis to the departments.

Outcome — Central team freed for the analysis only they can do.

Questions we are asked

Before you get in touch

Power BI or Tableau?

Usually whichever you already licence and staff. Power BI tends to win where Microsoft licensing is already in place; Tableau where visual exploration by analysts is the dominant pattern.

How do you decide what to retire?

Usage telemetry plus owner confirmation. Nothing is retired without a named owner agreeing, and we keep an archive.

Can BI and AI share a foundation?

They should. The same semantic layer that makes BI consistent is what stops an AI assistant giving a different revenue figure than the dashboard.

Start with three weeks and a straight answer

The AI Readiness Assessment is fixed in scope, fixed in price and produces four deliverables you own — whether or not you continue with us.