Accelerating Enterprise BI Migration: Domo to Microsoft Fabric

A US-based global chemical manufacturer with over 1,300 employees and 14 manufacturing plants across North America, Europe, and Asia. The company produces and distributes industrial and specialty chemicals, managing complex, high-volume financial operations globally.

Managing operational analytics across disparate manufacturing, supply chain, and financial systems presented critical migration hurdles.

• Preservation of Business Logic: Re-architecting complex calculations, Magic ETL transformations, and metric definitions from Domo without introducing data discrepancies.
• Manual Effort & Timeline Risks: Traditional manual rebuilds of hundreds of enterprise reports require extensive developer hours and delay time-to-value.
• System Performance Bottlenecks: Legacy BI reporting struggled to maintain fast query response times when processing large-scale operational data.
• Fragmented Data Governance: Domo's self-service model allowed individual teams to create siloed metrics independently, resulting in ungoverned data flows across sales, procurement, and inventory tools that hindered unified, enterprise-wide operational decision-making.

We modernized the entire analytics stack using QShift accelerator, combining agentic automation with confidence-based human validation. As a result, review effort went where it was actually needed rather than across every report by default.

• Rapid Migration Assessment & Roadmap: QShift's agentic assessment engine evaluated the client's complete Domo environment—including components, dependencies, and data flows. This generated a comprehensive migration roadmap with risk assessment and mitigation plans within 15 weeks, enabling informed go/no-go decisions before execution.
• Accelerated Logic Conversion: QShift extracted and translated complex Domo data models, Magic ETL workflows, calculation logic, and visualization layouts into native Microsoft Fabric assets, preserving business logic while significantly reducing manual migration effort.
• Intelligent Data Pipelines & Lakehouse: Automated ingestion, orchestration, staging, and streaming of enterprise data from applications, operational databases, and on-premises systems into SQL Server and Microsoft Fabric OneLake using Azure Data Factory and Power Automate, creating a unified, enterprise-ready data foundation.
• Power BI Visualization & Validation: Generated interactive Power BI dashboards directly connected to OneLake with optimized DirectLake performance. QShift automatically migrated high-confidence components, while lower-confidence components were routed through a human-in-the-loop review process for QBurst migration team approval before deployment.
• Centralized Governance: Replaced Domo's siloed, self-service metric definitions with governed, centrally managed data models in Microsoft Fabric, providing sales, procurement, and inventory teams with a single source of truth for enterprise reporting.

• Migration Stack: The migration pipeline moved data and logic through QShift as the agentic conversion engine, Azure Data Factory and Power Automate for ingestion, SQL Server for staging, Fabric OneLake as the lakehouse layer, and Power BI with DirectLake for reporting.
• Source Systems: Source content included Domo dashboards, Magic ETL pipelines, on-premise databases, and operational applications.
• Validation Mechanism: Both components and outputs were scored against a configured confidence benchmark, with items falling below the threshold routed to human-in-the-loop review and sign-off before promotion.
• Reporting Layer: Power BI reports ran in DirectLake mode, connecting directly to OneLake without intermediate data duplication between storage and report consumption.
• Governance Model: Data definitions were centralized within Fabric, replacing the per-team, self-service metrics that had previously fragmented reporting in Domo.

• Reduced Development Effort: Achieved a 30% reduction in development effort versus a fully manual rebuild, translating directly into lower overall project cost by pairing automated conversion for high-confidence components with targeted human validation at both conversion and output stages.
• Preserved Business Intelligence: Maintained 100% fidelity of legacy business logic and reporting metrics across finance, sales, and supply chain functions.
• Enhanced Query & Report Performance: Improved visual load times and analytics responsiveness by leveraging Microsoft Fabric's lakehouse architecture.
• Unified Data Governance: Eliminated the siloed, ungoverned metrics Domo's self-service model had produced, replacing them with centrally governed data definitions across the enterprise.