Big data: the management revolution.
Big data: the management revolution.
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发表时间：
2012-10
影响因子：
14.7
通讯作者：
Andrew P. McAfee;Erik Brynjolfsson
中科院分区：
文献类型：
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作者：
Andrew P. McAfee;Erik Brynjolfsson
作者写道，大数据比过去的分析要强大得多。管理人员可以比以往任何时候都更精确地衡量和管理。他们可以做出更好的预测和更明智的决定。他们可以在迄今为止由直觉和直觉而不是数据和严谨性主导的领域进行更有效的干预。大数据和分析之间的区别在于数量、速度和种类：现在每秒通过互联网的数据比20年前存储在整个互联网中的数据还要多。几乎实时的信息使公司比竞争对手更加敏捷。这些信息可能来自社交网络、图像、传感器、网络或其他非结构化来源。然而，管理方面的挑战是非常真实的。高级决策者必须学会提出正确的问题，并接受基于证据的决策。组织必须雇用能够在非常大的数据集中找到模式并将其转化为有用的业务信息的科学家。IT部门必须努力整合所有相关的内部和外部数据源。作者提供了两个成功的案例来说明公司如何使用大数据：PASSUR Aerospace使航空公司能够匹配其实际和预计的到达时间。Sears Holdings直接分析其传入的商店数据，使促销更加准确和快速。
Big data, the authors write, is far more powerful than the analytics of the past. Executives can measure and therefore manage more precisely than ever before. They can make better predictions and smarter decisions. They can target more-effective interventions in areas that so far have been dominated by gut and intuition rather than by data and rigor. The differences between big data and analytics are a matter of volume, velocity, and variety: More data now cross the internet every second than were stored in the entire internet 20 years ago. Nearly real-time information makes it possible for a company to be much more agile than its competitors. And that information can come from social networks, images, sensors, the web, or other unstructured sources. The managerial challenges, however, are very real. Senior decision makers have to learn to ask the right questions and embrace evidence-based decision making. Organizations must hire scientists who can find patterns in very large data sets and translate them into useful business information. IT departments have to work hard to integrate all the relevant internal and external sources of data. The authors offer two success stories to illustrate how companies are using big data: PASSUR Aerospace enables airlines to match their actual and estimated arrival times. Sears Holdings directly analyzes its incoming store data to make promotions much more precise and faster.