27 July, 2017
Learning To Do Distributed Big Data
For the last 10 years, businesses have tried to create value out of big data and advanced analytics based on a data lake approach, which is a centralized store of enterprise data that data scientists and others could “play” with. Sometimes this approach successfully generated big data returns. Too often it failed.
Nonetheless, the data lake concept was a reasonable approach because it economized on a variety of scarce assets, namely expertise, organizational attention, bespoke combination of analytic tooling and specialized big data systems. By accreting big data knowledge to a single, central location, a business could learn faster, make fewer mistakes and undertake advanced and complex analytics in a coherent way.