Enterprise Data Platform Implementation - Microsoft Azure and Fabric

The University of Portsmouth seeks an experienced implementation partner to design, build, and deploy a modern, enterprise-grade data platform to replace its legacy on-premises Oracle data warehouse. The new platform will be built on Microsoft Azure and Microsoft Fabric, providing a scalable, secure, and future-ready foundation for data ingestion, transformation, semantic modelling, reporting, and advanced analytics across the University. Scope: The project involves migrating approximately 1,200 ODI mappings, 35+ database schemas, and 3,000 tables. The platform must support approximately 4,000 internal users and indirectly serve 20,000+ students. Key deliverables include end-to-end architecture design, build, migration, comprehensive documentation, training, knowledge transfer, and production-ready operational handover. Key Objectives: Democratise data access through governed self-service capabilities, enabling teams across the University to access curated data models and develop solutions while maintaining strong governance standards. The platform should support both strategic and operational reporting, automated data updates, and self-service tools. Innovation Requirements: The supplier must deliver at least one proof of concept demonstrating advanced analytics capabilities in areas such as predictive analytics (e.g., student forecasting), advanced learning analytics, or data modelling for student recruitment and engagement. The specific use case will be defined collaboratively during delivery. Future Capabilities: The platform must be designed to support AI agents, large language model (LLM)-based natural language querying, and advanced learning analytics, enabling more intuitive and democratised access to insights. The University is interested in exploring innovative data applications alongside or following implementation, including forecasting and advanced insights. Delivery includes operational readiness support and structured transition to business-as-usual support, ensuring long-term sustainability and ongoing evolution of analytical capabilities.