Connectivity is the most widespread feature of today’s networks and systems. From protein interactions to social networks as Facebook or LinkedIn, from communication systems to electrical or power networks, and from economic grids as marketing or user bank systems to networks of neurons with even a moderate degree of complexity are not casual, which means it is not possible to assume any statistical distribution about connections of the networks mentioned above also because these are not static. Classical statistical analysis would be able neither to describe nor to predict behaviors within connected systems. As data becomes increasingly interconnected and systems increasingly sophisticated and complex, it is essential to make use of the rich and evolving relationships within our data, also using technologies built to leverage relationships and their dynamic nature.