University of Sheffield
Company Overview
The Center for Computational imaging & Simulation Technologies in Biomedicine (CISTIB) group based at the University of Sheffield performs cutting-edge research in areas of fundamental and applied biomedical imaging & modeling with impact in personalized minimally invasive therapies and active and healthy ageing. The team has an international and interdisciplinary profile and has a strong commitment to clinical and industrial translation with impact in future healthcare.
Challenge
The University of Sheffield’s CISTIB group wanted to learn more about the underlying pathology of dementia. They wanted to use a single Multix platform to analyze the rich library of unstructured biomedical data they had from over 6000 patients.
The platform needed to be able to move and maintain the unstructured data, easily and efficiently, between 8 different cloud providers (Amazon Web Services, Azure, Private Cloud) and 6 HPC Providers (Dell EMC Isilon) so that it could be analyzed by over 950 different applications.
Solution
The CISTIB group looked at a number of different vendors to transfer and replicate data on an ad-hoc basis and during live synchronizations from on-premises to supporting cloud providers. They compared WANdisco’s technology to a number of alternatives and found that WANdisco was the only solution that could transfer continually changing data to the cloud but also do it at the speed and volume they required.
“This project wouldn’t be possible without moving around large volumes of data that is heterogenous and changing over time.”
Alejandro Frangi, Professor of Biomedical Image Computing, The University of Sheffield
Results
- WANdisco offered the most impressive data migration performance in the market and was the only solution offering active-active WAN replication.
- WANdisco was found to be more resilient than other alternatives and was the only vendor solution which offered automatic recovery and guaranteed consistency.
- With WANdisco’s technology, the CISTIB can analyze unstructured patient data, whether in terms of primary or original data (e.g. medical histories, radiological information, etc.); secondary or derivative data from analysis and exploitation; or even metadata associated with patient’s genetic or therapeutic information.
