The Masters of Big Data

Humankind nowadays collects information in an unprecedented way: zillions of bits and bytes piling up to what is commonly referred to as “Big Data”. Societies become more and more dependent on their ability of handling, interpreting, and making sense of this information.

Large and comprehensive data sets can help us understand phenomena as diverse as the finance and banking sector, the evolution of friendship networks or the vulnerability of ecosystems. But data offer more possibilities: For the first time in history we not only start to understand the functioning of complex systems, but have the tools at hand to model them. This allows us to make predictions. And further it gets: With the help of supercomputers we can start simulating reactions and (unintended) consequences of interventions in a given complex system without the costly trial-and-errors in real life.

But to gain such far reaching insights into complex systems and eventually find ways to change them sustainably – that is, to use Big Data in a quantitative and predictive way – there is an urgent need for new mathematical concepts and methodology.

Big Data needs Big Theory.

This endeavor lies at the very heart of CSH Vienna’s research.