While astronomy is largely considered a pioneering discipline in data science and big data, several topics of astronomy still suffer from scarcity and inhomogeneity of data. I will focus on the current state of the field of Stripped Envelope Supernovae: these are a neglected sibling of the cosmological explosions and, thus far, they have largely been neglected observationally. Stripped SN (Ib, Ic, IIb and broad lined Ic SN) are the death throes of massive stars, and are connected to GRB explosions in ways yet to be fully understood. With the largest photometric and spectroscopic dataset of stripped SN to date in hand (Bianco+ 2014, Modjaz+ 2014) we move from a more traditional event by event approach to a statistical study of explosion observables and confront in this way the problem of connecting explosions to their progenitors. We also try to set the stage for the analyses that will be enabled by the wealth of data that the next generation of time-domain surveys will provide. I will also discuss the potential for LSST to impact SN science, both for cosmology and SN physics, and the current, concrete risk that LSST's impact will be underwhelming.