Astrophysics is one of the most data intensive research fields of the modern world and, as such, provides a unique context to drive many of the required innovations in the “big data” regime. In particular, radio astronomy is foremost in the field in terms of big data generation, and thanks to sustained global investment in the discipline over the last decade, present telescopes generate tens of petabytes of data per annum. The pinnacle of this so-called on-going ‘radio renaissance’ will be the Square Kilometre Array (SKA) — a global observatory tasked with probing the deepest mysteries of the Universe. The SKA will create the highest resolution, fastest frame rate movie of the evolving Universe ever and in doing so will generate 160 terrabytes of raw data a day, or close to 5 zettabytes of data per annum. These data will be processed into of order 1 petabyte of image cubes per day which will be processed, curated, and ultimately distributed via a network of coordinated tiered compute facilities to the global astronomical community for scientific exploitation. However, this truly data-rich environment will require new automated and semantic processes to fully exploit the vast sea of results generated. In fact, to fully realize the enormous scientific potential of this endeavour, we will need not only better data tagging and coordination mechanisms, but also improved algorithms, artificial intelligence, semantics and ontologies to track and extract knowledge in an automated way at a scale not yet attempted in science. In this keynote I will present an overview of the SKA project, outline the “big data” challenges the project faces and discuss some of the approaches we are taking to tame this astronomical data deluge.