Unified Architectural Data Aggregator

Streamlining data integration across varies sources and structures.

The Customer

UZ Leuven is an academic hospital in Leuven, Belgium, associated with KU Leuven. It consists of three campuses (as of 2022), providing approximately 2000 beds and enrolling 9000 employees. It is part of the Flemish Hospital Network KU Leuven, which is a partnership of 30 Flemish hospitals. KU Leuven is the biggest hospital in that partnership.

The Problem

Fragmented Data Sources: UZ Leuven faces the challenge of managing clinical data dispersed across multiple sources such as KWS (Sybase), LWS (Sybase), FHIR Datastores, Peoplesoft, eCFR and Formaza Documents (XML), leading to inefficiencies in data access and utilization.

The Goal

To establish a Centralized Data Warehouse UZ Leuven aims to develop a future-proof, scalable and secure Data Warehouse solution to consolidate clinical data from different sources. This initiative seeks to streamline data management processes and ensure governed access for researchers, doctors and clinical support managers (CSMs), fostering efficient and effective data-driven decision-making within the organization.

The Steps


Discover & Inspire

Tensr organised workshops to discover existing challenges and understand the as-is situation. Important aspects that were focused on include:

  • Current architecture
  • Existing tools and technologies
  • Existing technical expertise
  • Functional and technical requirements (legal, performance, standards, …)


Strategise & Ideate

Through interactive workshops we collaborated with the customer to build a high level architecture that could be reviewed and implemented by relevant teams such as infrastructure, networking and security.

Further workshops with more specialised teams served to ideate about how the data platform could be used to replace or improve on existing tools and processes. Through brainstorming sessions and workshops, we were able to point towards existing tools inside or outside GCP to solve a number of challenges (intelligent anonymisation, best practices on observability, issue management, data cataloging, etc).



To illustrate some concepts, we provided prototype samples which could be used to discuss internally, certain concepts and investigate how they could be used as more efficient or robust solutions to existing scripts.



The customer prefered to build and deploy the solutions themselves. Tensr is ready to assist as both a support or an implementation partner if desired by the customer.



Deploying the solution and integrated it with the customer’s existing systems.


Support & Train

Provide ongoing support and maintenance for the solution and develop standard operating procedures and training materials.

The Solution

As a result, Tensr delivered a detailed description of the suggested future data platform from an architectural, functional and security perspective. Subsequent workshops provided the customer with the necessary tools to take full ownership of the project, taking into account Google best practices, industry-specific requirements and the highly sensitive nature of the data.

The Architecture

Customer gain

The implemented solution instils confidence in scalability and compliance is instilled within the customer. National and industry-specific policies are seamlessly adhered to. Furthermore, the platform actively enhances data quality for various users by introducing a standardized model. While not hindering the autonomy of business users who can still effectively do what they do best.