What we do
We complement the traditional linear trajectory of investigation (i.e., developing a hypothesis, planning experiments, and collecting and analyzing data to test the hypothesis) with an iterative framework using data-driven and process-based approaches combined with novel complex-systems tools.
How we do it
These complex-systems tools find patterns that stand out from background noise in a large sets of data and deal with this complexity in Big Data sources. These sources are existing and newly collected data that have: a lot of data, almost real-time data, very different data types, data of varying quality and/or data ready for use.