Inverting 80/20: Beyond Bespoke Big Data
The past decade has seen a proliferation of standalone-tools and technology for large scale data processing. While powerful and transformational, the onus is still on the implementer to do most of the work – 80% of the time is spent on setting up the technology, leaving only a fraction to work on the actual problem at hand. In the early days of computing, every piece of software had this problem – until operating systems heralded a revolution in building applications cheaply. What does the same innovation look like in the big data space? How do we get beyond building prototype after prototype? And what about the elephant that’s not even in the room yet – namely, good user Interface?
