Six siloed systems unified into a single governed Fabric platform — consistent KPIs, reliable reporting, and issues caught before users see them.
Seven moves took finance, projects, timesheets, budgets, and operations from six disconnected systems to a single Fabric platform the whole business reports from. Follow the pipe.
Scroll to run the migrationSix independent systems covered finance, project management, timesheets, budgets, and operations, and each department reported off its own extract. There was no central version of the truth for project or financial KPIs.
Each system produced its own extract. No central version of the truth.
Data issues and refresh failures happened often with no visibility into root cause, and the gaps between systems were closed by hand. Business users couldn’t self-serve, and leadership had no single view of project performance, burn rate, or budget health.
Failures were discovered downstream, and the gaps were closed by hand.
The analytics foundation was rebuilt on Microsoft Fabric using our STEAM framework — a governed medallion architecture across ingestion, cleansing, and gold-layer business logic, ingesting and unifying all six systems in one place.
Ingestion, cleansing, and business logic separated — all six systems in one place.
A centralized star schema became the enterprise model for reporting, with over 100 KPIs defined directly in it — so projects, budgets, hours, and financials are measured the same way everywhere.
Over 100 KPIs defined once and reused everywhere.
Transformation logic was structured and instrumented — quality checks at each step and transparent lineage from source system to report, so any figure can be traced back to where it came from.
Any figure can be traced back to the system it came from.
Run statistics, row counts, and loading dashboards made pipeline health visible, and automated alerts notify the BI team of failures, delays, and anomalies before users notice them.
Issues surface early — troubleshooting starts before a ticket is raised.
A governed semantic model was exposed to analysts and business teams, designed for self-service rather than extract requests — removing manual Excel work and reducing dependency on IT.
Analysts build their own reporting on a model the business trusts.
Building an enterprise-grade business intelligence platform is no small undertaking, and finding a partner who can match both the technical complexity and the operational reality of your business is even harder. Dataracity did both. They navigated integration challenges across six disparate systems without losing sight of the bigger picture, and their command of the Microsoft stack meant we weren't spending cycles educating them on fundamentals. What set them apart was the strategic layer they brought — they weren't just executing tasks, they were thinking alongside me about what this platform needed to do long-term. We now have end-to-end operational metrics with clarity we've never had before — leadership can directly connect that data to P&L performance in real time. I would recommend Dataracity without hesitation.
Arthur L. Burris Jr.Director, Enterprise Architecture, BI & Process InnovationA small delivery team, named and accountable from kickoff to go-live.
Luke Matthews
Co-Founder, Head of Project Delivery & Data Architecture
Amanda Buthelezi
Co-Founder, Project Lead (BI & Data Strategy)
Boris Keckarovski
Data Engineer & Business Intelligence Consultant
Filip Bukvić
Business Intelligence Consultant
Bring us your systems and the KPIs that never agree. We'll map the unified architecture, the enterprise model, and the path to self-service in one conversation.
