As companies like Google, Facebook and Tesla push the envelope on new technologies like artificial intelligence, virtual reality and machine learning, it's tempting for older companies to try and reap the benefits. But often, due to decades of operating, these companies are overburdened by massive amounts of legacy data, scattered across dozens or hundreds of systems.
This data is gumming up their attempts at trustable analytics. The largest enterprises are realizing that in order to use to get to a place where they can use the latest and greatest technologies, they have to get their data in order.
This paper, by Turing Award winning computer scientist Michael Stonebraker, outlines the rapid, flexible and accurate approach of Scalable Data Mastering.