Modernize aging data marts and departmental warehouses on Microsoft Fabric. ETL rebuilds in Data Factory, storage moves to Lakehouse and OneLake, and Power BI serves governed reporting on top.
Every component of your legacy data marts estate maps to Power BI and Microsoft Fabric. Nothing is left behind, and everything is validated against the original.
The same structured methodology behind 1,200+ migrated reports. Validated side by side, documented, and delivered with zero disruption.
Inventory every report, data source, and dependency. Usage analysis identifies what actually matters.
Retire duplicates and unused reports. Typically 30 to 50 percent never need migrating.
Rebuild on Power BI and Fabric with governed semantic models and validated outputs.
Workspaces, row-level security, certified datasets, and documented standards.
Training and handover so your team owns the platform, not a vendor.
The free migration assessment inventories your legacy data marts estate, sizes the effort, and gives you a phased roadmap with costs. No commitment required.
Both are Fabric stores on OneLake. We typically land data in Lakehouse for flexibility and serve dimensional models through Warehouse or Direct Lake semantic models, decided per workload in the assessment.
Packages are inventoried and rebuilt as Data Factory pipelines and dataflows. Where wholesale rebuild is premature, SSIS can run interim via the Azure integration runtime while conversion proceeds in waves.
Consumers are cataloged first. Marts run in parallel with Fabric during migration, outputs reconcile row by row, and each report cuts over only after validation.
Yes. Conformed dimensions and governed measures in shared semantic models replace department-by-department copies, which is where the conflicting-numbers problem actually gets fixed.
A single mart with its ETL typically modernizes in 3 to 6 months. Multi-mart estates run as a program with a shared foundation wave first.
Tell us about your legacy data marts estate. A senior migration specialist will respond within one business day.