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Data Platform Implementation Partner Tender - 139750962

The UNIVERSITY OF PORTSMOUTH HIGHER EDUCATION CORPORATION has issued a Tender notice for the procurement of a Data Platform Implementation Partner in the United Kingdom. This Tender notice was published on 18 Apr 2026 and is scheduled to close on 13 May 2026, with an estimated Tender value of Refer Document. Interested bidders can access detailed Tender information, eligibility criteria, and complete bidding documents by referencing TOT Ref No. 139750962, while the tender notice number is 25-528 and Registering on the platform.

Expired Tender

Procurement Summary

Country: United Kingdom

Summary: Data Platform Implementation Partner

Deadline: 13 May 2026

Posting Date: 18 Apr 2026

Other Information

Notice Type: Tender

TOT Ref.No.: 139750962

Document Ref. No.: 25-528

Competition: ICB

Financier: Self Financed

Purchaser Ownership: Public

Tender Value: Refer Document

CPV Classification

71600000 - Technical testing, analysis and consultancy services
72000000 - IT services: consulting, software development, Internet and support

Purchaser's Detail

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Tender Details

The University of Portsmouth is seeking to design, build and implement a modern, enterprise-grade data platform to replace the existing on-premises Oracle data warehouse. The new platform will provide a scalable, secure and future-ready foundation capable of supporting the full ecosystem of data ingestion, transformation, semantic modelling, operational reporting, strategic insights, and AI-enabled analytical capabilities. The platform will form a critical foundation for decision making across the University, supporting academic operations, student lifecycle management, finance, HR, research and other domains. It will empower approximately 4, 000 internal users while indirectly supporting services that impact more than 20, 000 students. The solution will be developed using Microsoft Azure and Microsoft Fabric as the strategic technology stack. It must deliver high levels of scalability, improved data accessibility, and automation, alongside advanced analytics capabilities. The platform will also be designed to support future integration of AI agents and LLM-based natural language querying, enabling more intuitive and democratised access to insights. As part of its broader analytical capability, the platform should provide the foundations to enable advanced learning analytics and support data modelling use cases aligned to student recruitment, retention and engagement. There is an expectation that the delivery will include at least one agreed proof of concept to demonstrate the ...

Documents

 Tender Notice


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