Foreword [达文波特序言英文原文 This book is an important one for Chinese government and business organizations Big data and analytics based on it promise to change virtually every industry and business function over the next decade. Any organization that gets started early with big data can gain a significant competitive edge. Just as early analytical competitors in the" small data era(including Capital One bank, Progressive Insurance, and Marriott hotels)moved out head of their competitors and built a sizable competitive edge, the time is now for firms to seize the big data opportunit The pervasive future of big data is enabled by the pervasive nature of sensors and microprocessors today. We are entering into the ubiquitous computing age now. virtually every mechanical or electronic device can leave a trail that describes its performance, location, or state. These devices, and the people who use them, communicate through the Internet-which leads to another vast data source. When all these bits are combined with those from other media-wireless and wired telephony, cable, satellite, and so forththe rs even bigger. The availability of all this data means that virtually every business or organizational activity can be viewed as a big data problem or initiative. Manufacturing, in which most machines already have one or more microprocessors, is already a big data situation Consumer marketing, with myriad customer touchpoints and clickstreams, is already a big ata problem. Google has even described the self-driving car as a big data problem. overnments have begun to recognize that they sit on enormous collections of data
that wait to be analyzed. We can see big data and analytics initiatives ng governments in Asia. Last year, Singapore helped to launch the Deloitte Analytics Institute(DAD). Thi new institute is sponsored in part by the Economic Development Board of the Singapore he DaI's goal is to do research and thought leadership on the application of analytics to government and business. Singapore has also sponsored several university based research initiatives on analytics and big data Organizations that want to pursue big data opportunities need to begin working long several fronts, From a technology standpoint, they need to acquire and develop tools to manage both structured and unstructured data in massively parallel server environments, either on premise or in the cloud. They need to select analytical software to make sense of the data. Perhaps most importantly, they need to hire or develop the human talent to manage and analyze big data. These people are typically known as" data scientists"-hybrids of hacker and quantitative analyst-and they are in extremely short supply. Some companies are beginning to realize the extent of the opportunity, and to act upon it now. GE, for example, has committed to spend more than $1.5 billion to develop its Global Software and Analytics Center in the San Francisco Bay Area as a part of its Global Research organization. The company plans to hire at least 400 computer and data scientists at this location, and has already hired 180 Globally ge has over 10,000 engineers engaged in developing software and analytics products and services, and their efforts will be coordinated through common analytics platforms, training and leadership education, and innovative offerings. A significant portion of big data activities at GE will be focused on industrial products, such as locomotives, turbines, jet engines, and large energy generation facilities The size and ambition of GE's commitment should set the tone for other organizations that want to succeed with big data. Chinese government agencies and firms are noted worldwide for their ambitious plans in other domains, and these should be extended to big data. Zipei Tus book will help to guide government and business organizations efforts in this important area Thomas H. Davenport 大数据
目录 序言 大数据:为华文世界提出一个重要话题/许倬云 序言二中国的雄心应该拓展到大数据领域/托马斯·H·达文波特 序幕新总统的第一天 00l 人一票:把“黑”人送进“白”宫 大国新政:阳光是最好的防腐剂 07 上篇帝国风云…013 第一章历史争战《信息自由法 015 第四股力量:知情权的起点 国会议员:孤独的战争…01 白宮当家人:一个妥协者和机动者 政府VS.社会:旧剧情重现新时代…028 第二章数据帝国的兴起∴033 摩尔定律:全世界半个世纪的发展规律…034 最小数据集:上升到立法高度的开路先锋 041
民意几时有:选票催生的创新 普适计算:计算机本身将从人们的视线中消失…050 “大数据”战略:争夺全世界的下一个前沿 054 第三章数据治国 061 循“数”管理:平安大道怎样铺…03 数据“验”平权:民权史上的碑石……07 数据“打”假:最大的争议就是福利滥用 074 CompStat:街头警察的创新传奇…077 第四章商务智能的前世今生 起源:从数据到知识的挑战和跨越 结蛹:数据仓库之厚积薄发…090 蚕动:联机分析之惊艳 093 破茧:数据挖掘之智能生命的产生…097 化蝶:数据可视化的华丽上演
中篇法则博弈 113 第五章帝国的法则 115 收集法则:减负,为人民减负 使用法则:隐私,文明社会的共 121 发布法则:免费,人民已经交税 管理法则:质量,互联网时代的根本 131 第六章《数据质量法》的困局……135 产业界“俘虏”政府:数据背后的政经战争 美式“旋转门”:权、名、利大串场… “掺沙子”法案:国会对付总统的独门秘器…142 环保“风险门”:公共利益常常无人代表…14 集体行动的逻辑:人人都想“搭便车”…149 权之歧:什么是真正的“和谐”……152 第七章全国隐私风波 157 《一九八四》:零隐私的恐惧….157 大数据就是“老大哥”:中央数据银行之争…159 百年纠结:统一身份证 9·11”大拐点:以反恐的名义向左转 168 数据