When Google Inc. and the US Centers for Disease Control and Prevention first published information on ‘Google Flu’ in 2008, we were getting a foretaste of the knowledge and power incorporated in web search logs. In a nutshell, the project is based on a correlation between users’ flu related queries and the intensity of flu activity in particular regions. Google Flu Trends enables the aggregation of “Google search data to estimate current flu activity around the world in near real-time”. The notion of real-time predictions is highly significant in this context, since it differentiates this big data approach from conventional quantitative methods. A recent paper by the economists Tobias Preis, Helen Susannah Moat and Eugene Stanley takes the possibilities of analyses based on Google search data even further: Instead of relating health issues to users’ Google search requests, they presented a potentially profitable correlation between search terms such as “debt” and stock market developments. The data used for their research was provided by Google’s public Trends service.