OLAPing and Mining Big Data is among one of the most attracting
research contexts of recent years. Essentially, this puts emphasis on how classical
OLAPing and Mining algorithms can be extended in order to deal with novel
features of Big Data, such as volume, variety and velocity. This novel challenge
opens the door to a widespread number of challenging research problems that
will generate both academic and industrial spin-offs in future years. Following
this main trend, in this paper we provide a brief discussion on most relevant open
problems and future directions on the fundamental issue of OLAPing and Mining
Big Data.
