Case Study

Achieving significant savings in time and effort with Nuvolos on a Swiss macroeconomics research project

The Challenge

At the University of St. Gallen in Switzerland, a research team led by Prof. Matthias Fengler, Prof. Winfried Koeniger, and other colleagues studies consumption patterns in the Swiss economy by exploiting the ‘big data’ made available through the records of direct and online payment providers. The complexity of this macroeconomics research project consists in the vast quantity of data requiring analysis, as well as in its on-going nature as students from all levels, from bachelor’s to PhD, come into and leave the project as part of their own university training. 

For such a project, managing onboarding of new collaborators can be a cumbersome task, never mind the server maintenance for the datasets and the practical effort of distributing the research results across the team participants. Since the research team is not huge, it could easily take one or more PhD students a considerable proportion of their time just engaging with this overhead. Fortunately for the St. Gallen research team, Nuvolos, the integrated cloud-based solution for computational research, is designed to relieve precisely these burdens and give them their valuable research time back.

The Solution

By using Nuvolos, the researchers have been able to save significant time and effort on the overhead of their scientific work. The platform’s speed and ease of use, allowing the users to simply deploy their favorite applications directly in the browser using state-of-the-art cloud technology, make working with large datasets contained on multiple computers a joy for research rather than a headache. As all the typical data science tools, from SQL to R, are first-class citizens in Nuvolos, there is no concern about having to (re)learn new methods. Researchers who prefer using MATLAB or other statistical applications can do so, so that each team member can work with the framework they are most comfortable with. 

Onboarding new members of the research team, for example newly joined PhD students, is easy as Nuvolos makes distributing the existing material – code, data, and applications alike – a matter of a few mouse clicks. Since the platform is fully cloud-based and maintained by the engineers at Nuvolos, the research team in St. Gallen and elsewhere is relieved of the burden of maintenance, which affords them all the more time to do their scientific work. Finally, Nuvolos’ support team is intimately familiar with the work of computational scientists and provides Prof. Fengler and Prof. Koeniger with prompt and well-informed support.

The Outcome

The St. Gallen research team studying consumption patterns in the Swiss economy has given themselves their scientific work time back by using the Nuvolos computational science platform. Unlike many similar research teams, they do not need to occupy multiple PhD students’ time simply with acting as IT administrator and maintainer in order to be able to use a major dataset across multiple computers, nor with the overhead of configuring and setting up their familiar data science applications such as R. They onboard new students (and colleagues, for that matter) as needed using the platform and can immediately distribute all necessary data, code, and applications to them. Since Nuvolos can be accessed from anywhere, the typical research life on the move is no hindrance to getting work done on the platform. And not least of all, it’s fast – even very large data queries work without a hitch on Nuvolos’ built-in support for table operations. 

For the St. Gallen team, Nuvolos has proven its value. As Professors Fengler and Koeniger put it, reflecting the experience of their PhD students: “I can recommend Nuvolos to everybody who’s using more data than you store on one single computer. You can work with a big data set, and then you just need your laptop and you’re fine!”

Key Benefits

  • Fast and easy use of large datasets across multiple computers without worry about time spent on administration or overhead

  • Simple onboarding of new research team members through distribution of data, code, and applications in just a few clicks

  • Fast and knowledgeable support gives time back to the researchers to focus on their scientific work