
"Big Data" reveals how massive datasets are revolutionizing everything from flu prediction to crime prevention. Featured on the US Air Force's reading list, Oxford professor Mayer-Schonberger shows why correlation now trumps causation. Could your digital footprint predict your next purchase - or disease?
通过作者的声音感受这本书
将知识转化为引人入胜、富含实例的见解
快速捕捉核心观点,高效学习
以有趣互动的方式享受这本书
When Google tracked the 2009 H1N1 flu pandemic faster than the CDC by analyzing search queries, it signaled a fundamental shift in how we understand reality. This wasn't just clever technology-it was the dawn of the Big Data era. For most of human history, we've been forced to work with limited information. The 1880 U.S. census required eight years to process, making its insights obsolete before publication. These weren't just logistical problems but fundamental constraints on human knowledge. Today, those constraints have shattered. With billions of sensors, smartphones, and connected devices generating continuous data streams, we can analyze entire datasets rather than mere samples. Consider how Xoom, a financial services company, detected fraud by analyzing all transactions rather than investigating suspicious samples. They discovered subtle patterns that would have remained invisible using traditional approaches. This shift from sampling to comprehensive analysis fundamentally changes what we can know. Economist Steven Levitt's examination of 64,000 sumo wrestling matches revealed match-fixing patterns that would have been undetectable through sampling. Similarly, network analysis of millions of mobile phone connections showed that peripheral members with outside connections are more crucial to network stability than well-connected central figures-a counterintuitive finding that traditional methods would have missed. What makes this revolution particularly fascinating is its prescience. Written before terms like "data science" became household phrases, Big Data accurately predicted how information would transform everything from healthcare to criminal justice, fundamentally changing our relationship with information and decision-making.
将《Big Data》的核心观点拆解为易于理解的要点,了解创新团队如何创造、协作和成长。
将《Big Data》提炼为快速记忆要点,突出坦诚、团队合作和创造力的关键原则。

通过生动的故事体验《Big Data》,将创新经验转化为令人难忘且可应用的精彩时刻。
随心提问,选择声音,共同创造真正与你产生共鸣的见解。

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