【独家原文翻译56页版】麦肯锡大数据：创新、竞争和生产力的下一个前沿(原文翻译)
麦肯锡咨询：大数据在医疗行业(中英双语,译者E)
The role of big data in medicine November 2015Technology is revolutionizing our understanding and treatment of disease, says the founding director of the Icahn Institute for Genomics and Multiscale Biology at New York’s Mount Sinai Health System.Most companies make a conscious and deliberate decision to embrace digitization and the information revolution. Yet the role of big data in medicine seems almost to compel organizations to become involved. In this interview, Dr. Eric Schadt, the founding director of the Icahn Institute for Genomics and Multiscale Biology at New York’s Mount Sinai Health System, tells McKinsey’s Sastry Chilukuri how data-driven approaches to research can help patients, in what ways technology has the potential to transform medicine and the healthcare system, and how the Icahn Institute is building its talent base. An edited transcript of Schadt’s remarks follows.Evolution or revolution?The role of big data in medicine is one where we can build better health profiles and better predictive models around individual patients so that we can better diagnose and treat disease.One of the main limitations with medicine today and in the pharmaceutical industry is our understanding of the biology of disease. Big data comes into play around aggregating more and more information around multiple scales for what constitutes a disease—from the DNA, proteins, and metabolites to cells, tissues, organs, organisms, and ecosystems. Those are the scales of the biology that we need to be modeling by integrating big data. If we do that, the models will evolve, the models will build, and they will be more predictive for given individuals. It’s not going to be a discrete event—that all of a sudden we go from not using big data in medicine to using big data in medicine. I view it as more of a continuum, more of an evolution. As we begin building these models, aggregating big data, we’re going to be testing and applying the models on individuals, assessing the outcomes, refining the 医疗行业中的大数据2015.11“科技正在革新我们对于疾病的认识和治疗。
产业集群的外文翻译及原文(族群与集群竞争力)
英文文献资料（一）Clusters and the New Economics of CompetitionMichael E. Porter（Harvard university）Why Clusters Are Critical to CompetitionModern competition depends on productivity, not on access to inputs or the scale of individual enterprises.Productivity rests on how companies compete,not on the particular fields they compete panies can be highly productive in any industry–shoes, agriculture, or semiconductors – if they employ sophisticated methods, use advanced technology,and offer unique products and services. All industries can employ advanced technology; all industries can be knowledge intensive.The sophistication with which companies compete in a particular location, however, is strongly influenced by the quality of the local business environment.1 Companies cannot employ advanced logistical techniques, for example, without a high quality transportation infrastructure. Nor can companies effectively compete on sophisticated service without well-educated employees. Businesses cannot operate efficiently under onerous regulatory red tape or under a court system that fails to resolve disputes quickly and fairly. Some aspects of the business environment, such as the legal system, for example, or corporate tax rates, affect all industries. In advanced economies, however, the more decisive aspects of the business environment are often cluster specific; these constitute some of the most important microeconomic foundations for competition.Clusters affect competition in three broad ways:first, by increasing the productivity of companies based in the area; second, by driving the direction and pace of innovation, which underpins future productivity growth; and third, by stimulating the formation of new businesses, which expands and strengthens the cluster itself. A cluster allows each member to benefit as if it had greater scale or as if it had joined with others formally – without requiring it to sacrifice its flexibility.Clusters and Productivity. Being part of a cluster allows companies to operate more productively in sourcing inputs; accessing information, technology,and needed institutions; coordinating with related companies; and measuring and motivating improvement.Better Access to Employees and Suppliers. Companies in vibrant clusters can tap into an existing pool of specialized and experienced employees, thereby lowering their search and transaction costs in recruiting. Because a cluster signals opportunity and reduces the risk of relocation for employees, it can also be easier to attract talented people from other locations, a decisive advantage in some industries.A well-developed cluster also provides an efficient means of obtaining other important inputs.Such a cluster offers a deep and specialized supplier base. Sourcing locally instead of from distant suppliers lowers transaction costs. It minimizes the need for inventory, eliminates importing costs and delays, and –because local reputation is important –lowers the risk that suppliers will overprice or renege on commitments. Proximity improves communications and makes it easier for suppliers to provide ancillary or support services such as installation and debugging. Other things being equal, then, local outsourcing is a better solution than distantoutsourcing, especially for advanced and specialized inputs involving embedded technology, information, and service content.Formal alliances with distant suppliers can mitigate some of the disadvantages of distant outsourcing. But all formal alliances involve their own complex bargaining and governance problems and can inhibit a company’s flexibility. The close, informal relationships possible among companies in a cluster are often a superior Arrangement.In many cases, clusters are also a better alternative to vertical pared with in-house units, outside specialists are often more cost effective and responsive, not only in component production but also in services such as training. Although extensive vertical integration may have once been the norm, a fast-changing environment can render vertical integration inefficient, ineffective, and inflexible.Even when some inputs are best sourced from a distance, clusters offer advantages. Suppliers trying to penetrate a large, concentrated market will price more aggressively, knowing that as they do so they can realize efficiencies in marketing and in service.Working against a cluster’s advantages in assembling resources is the possibility that competition will render them more expensive and scarce. But companies do have the alternative of outsourcing many inputs from other locations, which tends to limit potential cost penalties. More important, clusters increase not only the demand for specialized inputs but also their supply.Access to Specialized Information. Extensive market, technical, and competitive information accumulates within a cluster, and members have preferred access to it. In addition, personal relationships and community ties foster trust and facilitate the flow of information. These conditions make information more transferable.Complementarities. A host of linkages among cluster members results in a whole greater than the sum of its parts. In a typical tourism cluster, for example, the quality of a visitor’s experience depends not only on the appeal of the primary attraction but also on the quality and efficiency of complementary businesses such as hotels, restaurants, shopping outlets, and transportation facilities. Because members of the cluster are mutually dependent, good performance by one can boost the success of the others.Complementarities come in many forms. The most obvious is when products complement one another in meeting customers’ needs, as the tourism example illustrates. Another form is the coordination of activities across companies to optimize their collective productivity. In wood products, for instance, the efficiency of sawmills depends on a reliable supply of high-quality timber and the ability to put all the timber to use – in furniture (highest quality), pallets and boxes (lower quality), or wood chips (lowest quality). In the early 1990s, Portuguese sawmills suffered from poor timber quality because local landowners did not invest in timber management. Hence most timber was processed for use in pallets and boxes, a lower-value use that limited the price paid to landowners. Substantial improvement in productivity was possible, but only if several parts of the cluster changed simultaneously.Logging operations, for example, had to modify cutting and sorting procedures, while sawmills had to develop the capacity to process wood in more sophisticated ways. Coordination to develop standard wood classifications and measures was an important enabling step. Geographically dispersed companies are less likely to recognize and capture such linkages.Other complementarities arise in marketing. A cluster frequently enhances the reputation of a location in a particular field, making it more likely that buyers will turn to a vendor based there.Italy’s strong reputation for fashion and design, for example, benefits companies involved in leather goods, footwear, apparel, and accessories. Beyond reputation, cluster members often profit from a variety of joint marketing mechanisms, such as company referrals, trade fairs, trade magazines, and marketing delegations.Finally, complementarities can make buying from a cluster more attractive for customers. Visiting buyers can see many vendors in a single trip. They also may perceive their buying risk to be lower because one location provides alternative suppliers. That allows them to multisource or to switch vendors if the need arises. Hong Kong thrives as a source of fashion apparel in part for this reason.Access to Institutions and Public Goods. Investments made by government or other public institutions– such as public spending for specialized infrastructure or educational programs – can enhance a company’s productivity. The ability to recruit employees trained at local programs, for example, lowers the cost of internal training. Other quasi-public goods, such as the cluster’s information and technology pools and its reputation, arise as natural by-products of competition.It is not just governments that create public goods that enhance productivity in the private sector. Investments by companies –in training programs, infrastructure, quality centers, testing laboratories, and so on – also contribute to increased productivity. Such private investments are often made collectively because cluster participants recognize the potential for collective benefits.Better Motivation and Measurement. Local rivalry is highly motivating. Peer pressure amplifies competitive pressure within a cluster,even among noncompeting or indirectly competing companies. Pride and the desire to look good in the local community spur executives to attempt to outdo one another.Clusters also often make it easier to measure and compare performances because local rivals share general circumstances – for example, labor costs and local market access – and they perform similar activities. Companies within clusters typically have intimate knowledge of their suppliers’ costs. Managers are able to compare costs and employees’performance with other local companies. Additionally, financial institutions can accumulate knowledge about the cluster that can be used to monitor performance.Clusters and Innovation. In addition to enhancing productivity, clusters play a vital role in a company’s ongoing ability to innovate. Some of the same characteristics that enhance current productivity have an even more dramatic effect on innovation and productivity growth.Because sophisticated buyers are often part of a cluster, companies inside clusters usually have a better window on the market than isolated competitors do. Computer companies based in Silicon Valley and Austin, Texas, for example, plug into customer needs and trends with a speed difficult to match by companies located elsewhere. The ongoing relationships with other entities within the cluster also help companies to learn early about evolving technology, component and machinery availability, service and marketing concepts, and so on. Such learning is facilitated by the ease of making site visits and frequent face-to-face contact.Clusters do more than make opportunities for innovation more visible. They also provide the capacity and the flexibility to act rapidly. A company within a cluster often can source what it needs to implement innovations more quickly. Local suppliers and partners can and do get closely involved in the innovation process, thus ensuring a better match with customers’ requirements.Companies within a cluster can experiment at lower cost and can delay large commitments until they are more assured that a given innovation will pan out. In contrast, a company relying ondistant suppliers faces greater challenges in every activity it coordinates with other organizations –in contracting, for example, or securing delivery or obtaining associated technical and service support. Innovation can be even harder in vertically integrated companies, especially in those that face difficult trade-offs if the innovation erodes the value of in-house assets or if current products or processes must be maintained while new ones are developed.Reinforcing the other advantages for innovation is the sheer pressure – competitive pressure, peer pressure, constant comparison – that occurs in a cluster. Executives vie with one another to set their companies apart. For all these reasons, clusters can remain centers of innovation for decades.Clusters and New Business Formation.It is not surprising, then, that many new companies grow up within an existing cluster rather than at isolated locations. New suppliers, for example, proliferate within a cluster because a concentrated customer base lowers their risks and makes it easier for them to spot market opportunities. Moreover, because developed clusters comprise related industries that normally draw on common or very similar inputs, suppliers enjoy expanded opportunities.Clusters are conducive to new business formation for a variety of reasons. Individuals working within a cluster can more easily perceive gaps in products or services around which they can build businesses. Beyond that, barriers to entry are lower than elsewhere. Needed assets, skills, inputs, and staff are often readily available at the cluster location, waiting to be assembled into a new enterprise.Local financial institutions and investors, already familiar with the cluster, may require a lower risk premium on capital. In addition, the cluster often presents a significant local market, and an entrepreneur may benefit from established relationships. All of these factors reduce the perceived risks of entry – and of exit, should the enterprise fail.The formation of new businesses within a cluster is part of a positive feedback loop. An expanded cluster amplifies all the benefits I have described – it increases the collective pool of competitive resources, which benefits a ll the cluster’s members. The net result is that companies in the cluster advance relative to rivals at other locations.英文文献中文翻译（二）来源：哈佛商业评论Vol.76第6期 1998年作者：迈克·E. 波特出版时间：1998簇群与新竞争经济学(美）迈克·E. 波特为什么簇群对竞争至关重要?现代竞争取决于生产力, 而非取决于投入或单个企业的规模。
大数据--下一个创新、竞争和生产力的前沿
低I类型（误报）和II
类型（假阴性）错误
的可能性。
从一组训练数据集推
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机器学习技术。
用于找到未标记数据 中的隐形结构的机器 学习技术。
聚类分析属于无监督 式学习。
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预测销售规模或传染 性病人就诊的数量。
节性和剩余组件，可 以用于识别数据的周
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数据聚类
划分对象的统计学方
法，将不同的集群划 分成有相似属性的小 群体，而这些相似属
（三）现有趋势将继续推动数据增长 在各部门和地区之间，企业正在加快收集数据的步 伐，推动了传统的事务数据库的增长；医疗卫生等面向消 费者的行业中，多媒体的广泛使用刺激了大数据的持续扩 张；社交媒体的广泛普及以及物联网中应用的不断创新都 进一步推动了大数据不断增长……这些相互交叉的动力 刺激了数据的增长，并将继续推动数据池的迅速扩张。
网 络与 不同的 地理 位 址或纬度/经度坐标。
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统计技术经常用于判
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的概率（“零假设”），
收集、组织和说明数 据的科学，包括设计
通过A/B测试判断哪种 类型的营销材料会最
麦肯锡《中国的数字化转型：互联网对生产力与增长的影响》
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内容摘要
麦肯锡全球研究院 中国的数字化转型
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考虑到互联网的发展速度和各行业的运用程度， 预计2013年至2025年， 互联网将帮助中国提升GDP增长率0.3-1.0个百分点。 这就意味着， 在这十 几年中 ， 互联网将有可能在中国GDP增长总量中贡献7％到22％。 到2025 年， 这相当于每年4万亿到14万亿元人民币的年GDP总量。 互联网不仅可以成为未来几年中国经济的新引擎之一， 更加重要的是， 它 还将改变经济增长的模式。 过去20年来， 中国依靠巨额资本投资和劳动力 扩张的增长方式在长期来看是不可持续的。 而互联网能够在生产力、 创新 和消费等各方面为GDP增长提供新的动力。 由于互联网加快了有效市场机 制的形成， 加强了竞争， 最具效率的企业得以更快地胜出。 同时， 互联网让 信息更为透明， 有助于优化投资决策， 让资本配置更为有效。 它还可以推 动劳动力技能提升、 提高劳动生产率； 通过降低价格、 让人们获取信息更 为便捷， 以及带来各种各样的便利创造消费者剩余。 上述转变会带来某些 风险和冲击， 但最终将有助于中国实现更为可持续的经济增长模式。
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GDP, 2013
麦肯锡全球研究院
McKinsey Global Institute
China’ s digital transformation: The Internet’ s impact on productivity and growth
中国的数字化转型： 互联网对生产力与增长的 影响
2014年7月
麦肯锡全球研究院
1 中小型企业是非分支机构的独立企业。 在欧洲， 其员工数少 于250人， 在美国少于500人。 在中国， 中小型企业的定义通常 是少于1000名员工的企业。 小微企业员工少于250人， 相当于 其他国家的中小型企业。
2015中国创新的全球效应-中文版
麦肯锡大中华区
麦肯锡的大中华区分公司由北京、 香港、 上海、 深圳和台北分公司组成。 20年来， 麦肯锡在大中华地区完成了2000多个项目， 帮助本土领先企业改善管理技能和 提升全球竞争力， 同时也为寻求在本地区扩大业务的跨国企业提供咨询。 更多信 息请访问。
Copyright © McKinsey 版权所有 © 麦肯锡公司， & Company 2015 2015 年
中国创新势在必行
当下， 中国正置身于挑战重重的转型征程之中。 人口的快速老龄化， 债务水平的 不断增高， 固定资产投资回报的减少， 给中国经济带来了全新的压力。 由于人口老 龄化的加剧， 中国的劳动力人口预计今年将会达到峰值， 随后进入漫长的萎缩 期， 到2050年劳动力人口将会下降16 %。 到2030年， 中国的人口赡养比， 即非劳 动力人口 （老年人和儿童） 的占比将达到47%。 以人均GDP发展水平来看， 人口 老龄化的势头要远远快于日、 美等国。 与此同时， 中国的工资水平也在增长： 最近 五年的平均工资年增幅为11%， 目前水平是印度和越南的1. 5 倍以上。 举债投资也到了回报持续减少的阶段。 从 2007年到2014 年年中， 中国的债务对 GDP比例由158%上升至282 %， 高于美国、 德国等发达经济体。 新增债务中约有 2 房地产市场供应过剩是中国固定资产投资 三分之一集中于房地产及其相关行业 。 收益减少的原因之一。 中国的增量资本产出率 （ICOR， 即创造单位GDP所需的资 本量） 在1990年到2010年期间平均为3.4， 而近年来却上升至5.4， 表明创造每单 位GDP所需的资本量增加了60 %。 按此趋势发展， 到2030年， 中国的ICOR将比 其他 “金砖国家” （俄罗斯、 印度、 巴西） 目前的水平高出17%， 接近美国、 韩国等 发达经济体当前的数值。 基于上述趋势， 我们认为创新对于中国经济的长期可持续增长十分必要。 过去30 年间， 中国的经济增长依靠的主要是 “汲取创新” （Innovation sponge） 模式， 即 中国 通过大量吸收并改良国际先进的科技、 最佳实践和知识来追赶领先国家 3。 企业采取的具体做法包括外资直接投资、 购买设备和企业， 以及组建合资企业。 因此， 中国的知识密集型贸易额 （高科技产品和服务、 外商直接投资和商业服务等 产品服务） 目前位列世界第二 4。 如图1所示， 创新对 如今， 创新必须在中国经济的所有行业板块发挥更大作用5。 于经济增长的贡献 （以多要素生产率衡量） 近年来有所减少。 从1990到2010年， 多要素生产率贡献了40 %- 48 %的GDP增长。 而近五年， 多要素生产率仅仅贡献 了30 %的GDP增长， 或相当于每年 GDP增长的2.4个百分点， 为35年来的最低水 平。 从现在起到2025年， 为了将 GDP年增长维持在5. 5%- 6. 5%的水平， 中国需要 让多要素生产率对 GDP增长的贡献达到35%- 50 % （2- 3个百分点） 。 创新对于创造高附加值和高收入的就业机会也至关重要。 随着城市化持续推 进， 预计到2020年中国大城市人口将再增加1亿。 这意味着每年需要1000万个城 镇就业机会， 而制造业的就业人数却在不断减少。 为了应对这些挑战， 中国需要加快从 “汲取创新” 到 “领导创新” 的转变， 以实现 更多的突破性创新， 从而在全球市场上展开竞争。 实现这样的转型需要更全面、 更深入的理解中国的创新现状， 创新的核心优势， 以及如何借用过去30年积累的 创新动力。 政策制定者对此已经推出了一系列举措， 如 “互联网+” 旨在利用互联 网鼓励万众创新和商业流程创新。
大数据的经济学研究文献综述
大数据的经济学研究文献综述学院:金融学院班级：13金融学硕姓名：熊美兰摘要:本文从传媒经济本体研究、产业经济学视角下的传媒经济研究、传媒经济研究工具的创新等方面来管窥近年来该领域的主要关注点以及新趋势和新突破,同时关注传媒经济学科体系研究的最新发展。
本年度传媒经济研究主题较为集中，主要是探讨传媒产业的数字化生存、全媒体转型策略与路径。
演化经济学、制度经济学、计算机和通信技术等视角和方法的引人,更加凸显了传媒经济学“跨学科”和“融合”的特征。
关键字:全媒体；三网联合；大数据；云计算;传媒经济学一、引言2012年,Tｗitter上每天发布超过4亿条微博，Ｆacebｏｏk上每天更新的照片超过1０00万张，Fareｃasｔ公司用将近10万亿条价格记录来预测机票价格,准确率高达７5％,采用该系统购票,平均每张机票可节省５０美元Ｇartner 预测未来5年全球大数据将会增加8倍，其中８0%是非结构化数据2０1３年世界上存储的数据将达到1.2ZB（1ZB＝1024ＥB,１EB=1024PB,1PB=1024TB,1TB=1024GＢ),如果将这些数据刻录到ＣDＲ只读光盘上,并堆起来，其高度将是地球到月球距离的５倍2０11年,麦肯锡公司对全世界大数据的分布作了一个研究和统计,中国２０10年新增的数据量约为250PB，而欧洲约为20００PB，美国约为3500ＰB,大数据已经深深地充斥了人类经济社会的许多角落。
著名未来学家阿尔文托夫勒(１980)［1]很早就在其经典著作《第三次浪潮》中，将大数据热情地赞誉为第三次浪潮的华彩乐章，但是大数据成为高频词是最近一两年的事情。
随着社交网络“物联网”云计算的兴起，数据规模越来越大，2011年5月,全球知名咨询公司麦肯锡(Ｍckinsey aｎｄCｏmpaｎy)发布了《大数据: 创新、竞争和生产力的下一个前沿领域》[2]报告,标志着“大数据”时代的到来，指出数据已经渗透到每一个行业和业务职能领域，逐渐成为重要的生产因素; 而人们对于海量数据的运用,将预示着新一波生产率增长和消费者盈余浪潮的到来，２0１2年世界经济论坛发布了《大数据、大影响》[3]的报告,从金融服务、健康教育农业、医疗等多个领域阐述了大数据给世界经济社会发展带来的机会。
大数据,巨大的力
大数据，巨大的力作者：蒲姜霖来源：《大学生》2013年第14期报告：《Big data： The next frontier for innovation， competition， and productivity》发布：麦肯锡全球研究院（McKinsey Global Institute）麦肯锡全球研究院（MGI）成立于1990年，是麦肯锡公司的业务和经济研究部。
该院的使命是帮助商界、公共部门以及社会各界的领导人更好地了解全球经济发展趋势，为在关键领域的管理和政策提供决策支持。
在2011年，麦肯锡全球研究所发布了报告《大数据：下一个创新，竞争和生产力前沿》（简称《大数据》），讨论了大数据给商业和经济发展带来的新的可能性，并预测到2018年，仅美国就存在14万～19万数据深入分析人才的缺口。
一个600美元的磁盘能存下全世界的音乐；2010年全球手机使用量达50亿部；“脸谱”网上每个月发帖量300亿；到2011年4月，美国国会图书馆已储存了235TB的数据；全球消费者每年通过使用个人定位数据，节约6000亿美元；零售商因利用大数据，经营利润可能提高60%；到2018年，全球仅美国就需要创建14万～19万个数据深入分析岗位，以及150万精通数据分析的管理人才；我们的世界正经历一场前所未有的数据大爆炸。
这对我们来说到底意味着什么？何谓“大数据”？“大数据”是当下炙手可热的名词，各行各业都在挖掘大数据的价值。
很多公司在利用大数据方面都取得了成功。
比如，乐购挖掘了消费者的大量数据，在此基础上进行消费者市场划分和针对性的促销活动；亚马逊利用消费者的购买信息，向消费者进行个性化商品推荐，每当消费者浏览某商品时，Amazon都会通过协同过滤（collaborative filtering）机制，显示“您可能还会喜欢……”“购买此商品的顾客也同时购买……”之类的信息；菲律宾移动运营商Smart通过分析其渗透力、零售商覆盖率，以及城镇用户的平均工资水平等数据，将公司的业务重点放在具有最大潜力的小众市场……那么，“大数据”到底是什么呢？“大数据”是指超过现有一般数据处理软件抓取、储存、处理和分析数据的能力的数据。
【独家原文翻译56页版】麦肯锡大数据：创新、竞争和生产力的下一个前沿(原文翻译)
大数据：创新、竞争和生产力的下一个前沿（原文翻译）麦肯锡在2011年5月发布了一个关于大数据方面的报告：《Big data: The next frontier for innovation, competition, and productivity》，虽然是6年前的报告，但是今天读来，还是非常用指导意义。
报告分为两个版本，一个是概要版20页，一个是完整版156页。
正好最近看了一遍概要版，觉得收益甚大。
所以试着翻译一下，仅供参考。
标题：Big data: The next frontier for innovation, competition, and productivity译文：大数据：创新、竞争和生产力的下一个前沿第二页是关于MGI（麦肯锡全球研究院）的介绍，就不翻译了。
略。
Data have become a torrent flowing into every area of the global economy. 1 Companies churn out a burgeoning volume of transactional data, capturing trillions of bytes of information about their customers, suppliers, and operations. millions of networked sensors are being embedded in the physical world in devices such as mobile phones, smart energy meters, automobiles, and industrial machines that sense, create, and communicate data in the age of the Internet of Things. 2 Indeed, as companies and organizations go about their business and interact with individuals, they are generating a tremendous amount of digital“exhaust data,”i.e., data that are created as a by-product of other activities. Social media sites, smartphones, and other consumer devices including PCs and laptops have allowed billions of individuals around the world to contribute to the amount of big data available. And the growing volume of multimedia content has played a major role in the exponential growth in the amount of big data (see Box 1, “What do we mean by ‘big data’?”). Each second of high-definition video, for example, generates more than 2,000 times as many bytes as required to store a single page of text. In a digitized world, consumers going about their day—communicating, browsing, buying, sharing, searching—create their own enormous trails of data.译文：数据已成为流入全球经济各个领域的激流。
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大数据：创新、竞争和生产力的下一个前沿（原文翻译）麦肯锡在2011年5月发布了一个关于大数据方面的报告：《Big data: The next frontier for innovation, competition, and productivity》，虽然是6年前的报告，但是今天读来，还是非常用指导意义。
报告分为两个版本，一个是概要版20页，一个是完整版156页。
正好最近看了一遍概要版，觉得收益甚大。
所以试着翻译一下，仅供参考。
标题：Big data: The next frontier for innovation, competition, and productivity译文：大数据：创新、竞争和生产力的下一个前沿第二页是关于MGI（麦肯锡全球研究院）的介绍，就不翻译了。
略。
Data have become a torrent flowing into every area of the global economy. 1 Companies churn out a burgeoning volume of transactional data, capturing trillions of bytes of information about their customers, suppliers, and operations. millions of networked sensors are being embedded in the physical world in devices such as mobile phones, smart energy meters, automobiles, and industrial machines that sense, create, and communicate data in the age of the Internet of Things. 2 Indeed, as companies and organizations go about their business and interact with individuals, they are generating a tremendous amount of digital“exhaust data,”i.e., data that are created as a by-product of other activities. Social media sites, smartphones, and other consumer devices including PCs and laptops have allowed billions of individuals around the world to contribute to the amount of big data available. And the growing volume of multimedia content has played a major role in the exponential growth in the amount of big data (see Box 1, “What do we mean by ‘big data’?”). Each second of high-definition video, for example, generates more than 2,000 times as many bytes as required to store a single page of text. In a digitized world, consumers going about their day—communicating, browsing, buying, sharing, searching—create their own enormous trails of data.译文：数据已成为流入全球经济各个领域的激流。
公司制造了数量庞大的交易数据，捕获了数万亿字节的有关其客户、供应商和公司运营的信息。
数百万的网络传感器被嵌入在诸如移动电话、智能电表、汽车和工业机器等实体设备中，它们在物联网时代感知、创建和传送着数据。
事实上，随着公司和组织开展他们的业务并与个人进行互动，他们正在产生大量的“排放数据”，即作为其他活动的副产品而产生的数据。
社交媒体、智能手机和其他消费设备，包括PC和笔记本电脑，使世界上数十亿的个人能够贡献大量数据。
而且越来越多的多媒体内容在大数据的指数增长中发挥了重要作用（见插文1，“大数据”是什么？）。
例如，每秒的高清视频生成的字节数量是存储单页文本所需的2000倍。
在数字世界中，消费者每天都在进行通信、浏览、购买、共享和搜索——创建自己巨大的数据流。
Box 1. What do we mean by "big data"?“Big data”refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze. This definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big data—i.e., we don’t define big data in terms of being larger than a certain number of terabytes (thousands of gigabytes). We assume that, as technology advances over time, the size of datasets that qualify as big data will also increase. Also note that the definition can vary by sector, depending on what kinds of software tools are commonly available and what sizes of datasets are common in a particular industry. With those caveats, big data in many sectors today will range from a few dozen terabytes to multiple petabytes (thousands of terabytes).译文：插文1.“大数据”是什么？“大数据”是指数据量级超过传统数据库软件工具捕获、存储、管理和分析能力的数据集。
这个定义是主观的，并且包含了一个数据集量级的动态定义（超过这个大小才会被认为是大数据）——也就是说，我们没有定义一个确定的值（比如多少TB）。
我们认为随着技术的进步，被认定为“大数据”的数据集的大小数量级也将增加。
还要注意，这个数据集大小的定义会因行业而异，它取决于这些行业中普遍使用的软件工具不同以及通常的数据集的大小。
基于这些认知，今天许多行业的大数据的数据集大小范围将从几十TB到几PB（几千TB）。
In itself, the sheer volume of data is a global phenomenon—but what does it mean? Many citizens around the world regard this collection of information with deep suspicion, seeing the data flood as nothing more than an intrusion of their privacy. But there is strong evidence that big data can play a significant economic role to the benefit not only of private commerce but also of national economies and their citizens. Our research finds that data can create significant value for the world economy, enhancing the productivity and competitiveness of companies and the public sector and creating substantial economic surplus for consumers. For instance, if US health care could use big data creatively and effectively to drive efficiency and quality, we estimate that the potential value from data in the sector could be more than $300 billion in value every year, two-thirds of which would be in the form of reducing national health care expenditures by about 8 percent. In the private sector, we estimate, for example, that a retailer using big data to the full has the potential to increase its operating margin by more than 60 percent. In the developed economies of Europe, we estimate that government administration could save more than €100 billion ($149 billion) in operational efficiency improvements alone by using big data. This estimate does not include big data levers that could reduce fraud,errors, and tax gaps (i.e., the gap between potential and actual tax revenue).译文：数据量激增本身是一个全球现象，但它是意味着什么呢？全球范围内有许多人对这种信息收集持深深的怀疑态度，认为数据泛滥只不过是对他们隐私的侵犯。