我们看待数据的方式的两个变化——从局部变为全部以及从纯净变为凌乱——催生了第三个变化:从因果关系到相关性。这代表着告别总是试图了解世界运转方式背后深层原因的态度,而走向仅仅需要弄清现象之间的联系以及利用这些信息来解决问题。加拿大的研究人员正在开发一种大数据手段,以便能在明 Two changes in the way we look at data - from local to total and from pure to messy - spawn a third change: from causality to relevance. This means saying goodbye to always trying to understand the underlying causes behind the way in which the world works, and moving to just need to understand the linkages between the phenomena and use the information to solve the problem. Researchers in Canada are developing a big data tool to be clear