Business intelligence consulting for dashboards people trust
Power BI and KPI dashboards built on one governed semantic model, organized by the decision each role makes, and checked against whether anyone opens them.
- Power BI
- SQL
- Python
- PostgreSQL
- AWS
- React
- Existing reports
- Warehouse or replica
- Spreadsheet packs
- 01 Audit reportswhat is used, trusted, duplicated
- 02 Semantic modelone measure per agreed KPI
- 03 Dashboards per rolebuilt around one decision each
- 04 Usage reviewunused views removed
- Trusted KPI dashboards
- Automated report packs
- Access by role
What you get
8 deliverables, all yours to keep
- Report and dashboard audit
- Governed semantic model with shared measures
- KPI dashboards per role
- Automated report packs and alerts
- Row-level security by role and region
- Workspace and publishing standards
- Usage review and cleanup
- Handover guide for your report builders
Sound familiar?
When business intelligence consulting is the right call
Most organizations that ask for business intelligence consulting already have dashboards. What they do not have is agreement on the numbers in them. Revenue is calculated one way in the sales report and another way in the finance pack, so leadership keeps reading the spreadsheet a team assembles by hand every Monday.
We fix the model before the visuals: one governed definition per KPI, shared by every dashboard, then views built around the decisions each role makes. For a global AI SaaS company, that included executive KPI reporting and an automated reporting framework on top of a unified analytics platform. The definition work is the hard part, and we wrote about how that meeting usually goes.
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Three dashboards show three different revenue figures
Each report calculates the measure its own way, so meetings start with which number is right instead of what to do.
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Hundreds of reports, a handful actually opened
Every request became a new report. Nobody knows which ones matter, so nothing gets retired.
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The Power BI license is paid, the Excel pack still ships
Leadership still reads the spreadsheet a team assembles every Monday, because it is the version they trust.
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Dashboards break when a source column changes
Logic lives inside individual reports, so one upstream change breaks a dozen visuals nobody can trace.
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Everyone sees everything, or nobody sees anything
Without role and region security in the model, access is either too open to share or locked down until it is useless.
The work
Inside a Business Intelligence & Power BI engagement.
Power BI consulting and the model underneath it
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Report audit and rationalization
An inventory of existing reports with usage, owners and the measures each one calculates, so duplicates are merged and unused reports retired.
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Semantic model design
One governed model where each KPI is a shared measure with a written definition, instead of logic copied into every report.
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KPI dashboard development
Dashboards organized by role and by the decision each one supports, in Power BI or as custom dashboards where a product needs them embedded.
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Report automation
Scheduled report packs, subscriptions and threshold alerts that replace the spreadsheet a team assembles by hand.
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Security and workspace governance
Row-level security by role and region, workspace structure, publishing standards and naming, so self-service does not turn into sprawl again.
How we approach business intelligence consulting
- 01
Audit before building anything new
Most organizations already have more dashboards than they use. The first step is finding which reports are opened, which are trusted and which calculate the same measure differently.
- 02
The model is the product, not the visuals
Charts are easy to redraw. A shared semantic model with one measure per KPI is what keeps three dashboards from disagreeing, so that is where most of the effort goes.
- 03
One dashboard, one decision
Every dashboard gets a named role and the question it answers. A request with no decision behind it becomes a filter on an existing view, not a new report.
- 04
Use the tool you already pay for
If your finance team lives in Power BI, we build there. We only suggest custom dashboards when a view has to sit inside your own product or the licensing model does not fit the audience.
Where BI projects go wrong
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Rebuilding every existing report one for one
The audit decides what is migrated. Reports nobody opened in months are retired, and duplicates are merged into one view with filters.
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Measures redefined inside individual reports
KPI logic lives only in the shared model. Report builders use the governed measures, and a new definition goes through the metric owner.
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Self-service turns into sprawl again within a year
Workspace standards, certified datasets and a scheduled usage review keep the report estate small enough to trust.
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A dashboard that disagrees with finance on launch day
New figures are reconciled against the numbers finance already reports before a dashboard is published, and every difference is explained.
How it runs
From first call to production.
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Report audit
About a week. We inventory existing reports, check usage and ownership, and list every place the same KPI is calculated differently.
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Definitions and model
Metric owners agree one definition per disputed KPI, and those definitions become shared measures in a governed semantic model.
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Dashboards per role
Views are built for the roles and decisions on the list, reconciled against finance figures before anyone relies on them.
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Automation and security
Scheduled packs, alerts and row-level security replace manual exports and one-off sharing.
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Usage review
After a cycle, each dashboard is checked against whether it was opened and whether it changed a decision. Unused views are removed.
Team and timeline
2–4 weeks
to a first governed dashboard set in your BI tool
Indicative. Actual duration depends on requirements and complexity, and can change.
Who works on it
- Analytics specialist
- Data engineer
- Product consultant
- UX designer
Engagement model
Agile Time & Material, because the audit usually changes what is worth building. A Dedicated Team suits organizations that want a standing BI function to own the model after launch.
Good to know
Assumes an existing warehouse or read replica. If sources still need pipelines, Data Engineering & Analytics comes first. Your side provides BI admin access, the metric owners and a finance contact for reconciliation.
Proof
Where we have built this.
How a global AI SaaS company improved conversion rates by 18%
enhanced KPI visibility
How a leading construction enterprise improved vendor processing by 42%
faster vendor processing
How a large global financial services company reduced travel processing time by 38%
faster travel processing
FAQ
Business Intelligence & Power BI: common questions.
What does a business intelligence consulting engagement deliver?
A smaller, trusted set of dashboards rather than more of them. That means an audit of existing reports, a governed semantic model with one shared measure per KPI, dashboards built per role, automated report packs, row-level security, and a usage review that removes what nobody opens.
What is the difference between this and Data Engineering & Analytics?
Data Engineering & Analytics builds the pipelines and the modeled data layer from your source systems. Business intelligence consulting works on top of an existing warehouse or replica: the semantic model, the dashboards, report automation and governance. If your data is not yet in one place, the engineering work comes first.
Do you only work in Power BI?
No, but we use the tool you already pay for. Power BI is the most common. Where a dashboard has to live inside your own product, or a BI license across a large external audience is out of proportion, we build custom dashboards on the same governed model.
Can you fix our existing Power BI reports rather than starting over?
Usually, yes. The audit shows which reports are used and trusted. Those are moved onto the shared semantic model, duplicates are merged and unused reports retired. A full rebuild is only worth it when the logic inside the existing reports cannot be traced.
How long does a BI engagement take?
A first governed dashboard set typically takes 2–4 weeks when a warehouse or read replica already exists. Actual duration depends on requirements and complexity, and can change. Larger report estates are cleaned up in slices, with the most used dashboards moved first.
Related services
- Data Engineering & AnalyticsData analytics consulting and data engineering for teams that have the data but cannot answer the question. One definition per metric, reporting that runs itself.
- AI DevelopmentLLM applications, generative AI features and document agents built for production: structured outputs, pinned models, regression sets and a person on every consequential decision.
- Dedicated Development TeamA dedicated development team or individual engineers who join your sprints and your tools. We handle selection, ramp-up, cover and continuity.
Further reading
