大数据英语PPT
Part 6 conclusion
Part 6
intelligence.
conclusion
Data on today’s scales require scientific and computational Big Data Future is a free, public, multidisciplinary conference on
transportation
TransDec (Transportatironic health record
EHRs offer plenty of data—test results, diagnoses, prescriptions, emergency room (ER) visits, previous hospitalizations, demographic information. The software works by sifting through records of patients who were previously hospitalized and learning which risk factor—a certain number of chest complaints or an unusual level of a particular enzyme in the heart, for example—might have been red flags. The algorithm then uses those red flags to warn of future hospitalizations.
fig. New types of research data about human behavior and society pose many opportunities if crucial infrastructural challenges are tackled.
5
Words and sentences
Big data
computer specialty
Taobao search
definition
definition
Big data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture ,manage and process the data within a tolerable elapsed time.
这个趋势在撒哈拉以南尤其令人印象 深刻，这里的移动电话技术已经被用 来作为弱电信和交通基础设施以及欠 发达的银行和金融系统的替代品。
（）：定语，修饰Sub-Saharan Africa （）：介词 （）：并列作用
sentences
2、（Initially developed in such fields as computational biology , biomedical engineering, medicine, and electronics, ） Big Data analytics refers to （tools and methodologies） that （ aim to transform massive quantities of raw data into “data about the data”—for analytical purposes）.
opportunities
opportunities
data revolution
The early years of data revolution:
today a massive amount of data is regularly being generated and flowing from various sources, through different channels, every minute in today’s Digital Age. Now: available digital data:150 EB(2005) 1200 EB(2010) Predicted: the stock of digital data is expected to increase 44 times between 2007 and 2020, doubling evallenges
Data
privacy access and sharing
Analysis
“what is the data really telling us?” summarizing the data interpreting defining and detecting anomalies
the possibilities for new enterprises grounded in “big data” to
improve economic, social, and political life. What is needed is both intent and capacity to be sustained
ETL : Extract Transform Load，是指数据的提取、转换、加载。 Database : 数据库
sentences
1、The trend is especially impressive in Sub-Saharan Africa, （where mobile phone technology has been used as a substitute （for usually weak telecommunication and transport infrastructure ） （as well as underdeveloped financial and banking systems））.
and strengthened, on the basis of a full recognition of the
opportunities and challenges.
Thank you
（过去的）
Characteristics:
Volume : data size
Velocity :speed of change Variety : different forms of data sources
"Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization." ——Gartner
words
B2C : business-to-consumer 企业对消费者 Cookie : 指的是指网站为了辨别用户身份而储存在用户本地终 端浏览器上的一类数据。 TB : terabyte 1TB=1024MB PB : petabyte 1PB=1024TB EB : exabyte 1EB=1024PB
application
application
Bank transactions
1.3 million transactions in 2015 worldwide;
E-commerce
Taobao Amazon
Medical treatment
EHR (electronic health record);
最新Big-Data-大数据介绍(全英)ppt课件
Why ‘Big Data’ is a big Deal
Big data differs from traditional information in mind-bending ways: Not knowing why but only what The challenge with leadership is that it’s very driven by gut instinct in most cases Air travelers can now figure out which flights are likeliest to be on time, thanks to data scientists who tracked a decade of flight history correlated with weather patterns Publishers use data from text analysis and social networks to give readers personalized news. health care is one of the biggest opportunities, If we had electronic records of Americans going back generations, we'd know more about genetic propensities, correlations among symptoms, and how to individualize treatments.
Main steps in adopting an analytical system
大数据英文版
大数据英文版Title: Big Data: An OverviewIntroduction:Big Data has become a buzzword in today's digital era. It refers to the massive amount of data generated from various sources, which can be analyzed to reveal patterns, trends, and insights. This article provides a comprehensive overview of Big Data, covering its definition, characteristics, applications, challenges, and future prospects.I. Definition and Characteristics of Big Data:1.1 Volume:- Big Data refers to the vast amount of structured, unstructured, and semi-structured data that is generated every second.- It includes data from social media, online transactions, sensors, and other sources.- The volume of Big Data is measured in petabytes, exabytes, and zettabytes.1.2 Velocity:- Big Data is generated at an unprecedented speed.- Real-time data streams from social media, sensors, and other sources contribute to its velocity.- The ability to process and analyze data in real-time is crucial for deriving meaningful insights.1.3 Variety:- Big Data encompasses a wide range of data types, including text, images, videos, audio, and more.- It includes structured data from databases, semi-structured data from XML files, and unstructured data from emails, social media posts, etc.- The variety of data poses challenges in terms of storage, processing, and analysis.II. Applications of Big Data:2.1 Business Analytics:- Big Data analytics helps organizations gain insights into customer behavior, market trends, and competitive intelligence.- It enables businesses to make data-driven decisions, optimize operations, and improve customer satisfaction.- Predictive analytics and machine learning algorithms are used to identify patterns and predict future outcomes.2.2 Healthcare:- Big Data plays a significant role in healthcare by analyzing patient records, medical images, and genomic data.- It helps in disease diagnosis, personalized medicine, drug discovery, and healthcare resource management.- Real-time monitoring of patient data can detect anomalies and provide timely interventions.2.3 Smart Cities:- Big Data analytics is used in urban planning, transportation management, and energy optimization in smart cities.- It enables the collection and analysis of data from sensors, CCTV cameras, and social media to improve city services.- Predictive models can be created to optimize traffic flow, reduce energy consumption, and enhance public safety.III. Challenges in Big Data:3.1 Data Privacy and Security:- With the increasing volume and variety of data, ensuring data privacy and security becomes crucial.- Organizations must comply with regulations and implement robust security measures to protect sensitive information.- Techniques like encryption, access controls, and anonymization are used to safeguard data.3.2 Data Quality and Integration:- Big Data often comes from disparate sources, leading to data quality issues.- Data integration and cleansing techniques are used to ensure the accuracy and consistency of data.- Data governance frameworks are implemented to maintain data integrity and reliability.3.3 Scalability and Infrastructure:- Big Data requires scalable storage and processing infrastructure to handle large volumes of data.- Distributed computing frameworks like Hadoop and Spark are used to process data in parallel.- Cloud computing provides on-demand scalability and cost-effective solutions for Big Data processing.IV. Future Prospects of Big Data:4.1 Artificial Intelligence and Machine Learning:- Big Data and AI are closely intertwined, with AI algorithms driving insights from Big Data.- Machine learning techniques enable automated data analysis, pattern recognition, and predictive modeling.- The integration of Big Data and AI will continue to advance automation and decision-making.4.2 Internet of Things (IoT):- The proliferation of IoT devices generates massive amounts of data, contributing to Big Data.- IoT data combined with Big Data analytics can optimize processes, improve efficiency, and enable new services.- The integration of IoT and Big Data will revolutionize industries like manufacturing, transportation, and healthcare.4.3 Ethical Considerations:- As Big Data becomes more prevalent, ethical considerations surrounding data usage and privacy will gain importance.- Organizations need to establish transparent data governance policies and ensure responsible data handling practices.- The ethical use of Big Data will be crucial in maintaining trust and avoiding potential societal risks.Conclusion:Big Data is transforming the way businesses, industries, and societies operate. Its vast volume, high velocity, and diverse variety present both opportunities and challenges. By harnessing the power of Big Data analytics, organizations can gain valuable insights,make informed decisions, and drive innovation. However, ethical considerations and data privacy must be addressed to ensure responsible and sustainable use of Big Data in the future.。
《大数据专业英语》课件—01What Is Big Data
New Words
storage compute
[ˈstɔrɪdʒ] [kəmˈpju:t]
precise insightful predict predictive indication maximize
[prɪˈsaɪs] [ˈɪnˌsaɪtfʊl] [prɪˈdɪkt] [prɪˈdɪktɪv] [ˌɪndɪˈkeɪʃn] [ˈmæksɪˌmaɪz]
2.大数据的三V 2.1大量 数据量很重要。对于大数据，必须处理大量低密度、非结构化的数据。这可以是未 知价值的数据，例如Twitter反馈的数据，网页或移动应用上的点击流，或来自有效 传感器设备的数据。这可能是的数十TB的数据，而对其它组织，数据甚至可以达到 数百PB的量级。
参考译文
2.2高速 高速是接收数据并可能以此采取行动的速率很快。一些支持互联网的智能产品实 时或接近实时运行，需要实时评估和行动。
参考译文
4.2预测性维护 可以预测机械故障的因素可能深深地隐藏在结构化数据中，例如设备年份、品牌和 机器型号以及数百万个日志条目、传感器数据、错误消息和发动机温度等的非结构 化数据。通过在问题发生之前分析这些潜在问题的迹象，组织可以更经济地部署维 护并尽量延长部件和设备的正常运行时间。
4.3客户体验 争夺客户无时不在。现在比以往能更加清晰地了解客户体验。通过大数据，可以从 社交媒体、Web访问、呼叫日志和其它数据源收集数据，从而改善交互体验并最大 限度地提高交付价值。开始提供个性化优惠，减少客户流失，并主动处理问题。
format engine on-demand gradually popularity clarity explore discover
[ˈfɔrmæt] [ˈɛndʒɪn] [ɒn-dɪˈmɑ:nd] [ˈɡrædʒʊəlɪ] [ˌpɒpjuˈlærɪtɪ] [ˈklærɪtɪ] [ɪkˈsplɔ:] [dɪsˈkʌvə]
BIGDATA-大数据精品PPT课件
大数据的作用如何
• 谷歌的判断就建立在大 数据基础上：即以一种 特定方式，对海量数据 进行分析，获得有巨大 价值的产品和服务或深 刻的洞见。
大数据的作用如何
• 世界的本质是数据 • 案例1：2009年，甲型H1N1流感爆发的前几周，
谷歌的工程师在《自然》杂志上预测大型流感 传播即将到来。不需分发口腔试纸或调查医生， 他们建立了一个系统，在每天收到的数十亿条 搜索指令中关注特定检索词条（如“哪些是治 疗咳嗽和发热的药物”等）的频繁使用与流感 传播之间的联系，及时判断流感从哪里传出。 而疾控中心要到流感爆发一两周后才能确定。
19
大数据背后的价值
衍生于亚马逊、Google等互联网公司
互联网越来越智能 Google精确掌握用户行为、 获取需求
Facebook用户 产生内容，创造 需求。
Google分析用 户搜索信息，满 足用户需求 雅虎提供静态的 导航信息
告诉司机少左转
坐姿提醒你累了
蛋挞搭着飓风卖
错误数据也有用
混乱数据也有用
BIG DATA
分享人：
不知道BIG DATA?
你out了!
大数据
作
你
是
用
知
什
如
道么何吗 Nhomakorabea为
背
何
后
而
的
来
价
值
大数据是什么
除了上帝， 任何人都要用数据说话
Big Data时代到来
在web 2.0的时代，人们从信息的被动接受者变成了主动创造者
全球每秒钟发送 2.9 百万封电子邮件，一分钟读一篇的话，足够一个人昼夜不息的读5.5 年… 每天会有 2.88 万个小时的视频上传到Youtube，足够一个人昼夜不息的观看3.3 年… 推特上每天发布 5 千万条消息，假设10 秒钟浏览一条信息，这些消息足够一个人昼夜不息的浏览16
BIG DATA 大数据 英文演讲ppt
becoming an important production factor.
Big data: Taobao transaction volume
Fourth: The industrial Internet will drive big data to the ground. Big data is a focus of industrial Internet development, big data can land in traditional industries, Related to the development process of industrial Internet, so in the industrial Internet stage, big data will gradually land, but also will inevitably land.
Gather Data
AnGaatlhyezre DDaattaa
EAT
SPICY
HCHOINTESPEDORDIRNPINKK
RESTAURANT
Driving route planning
Discount push
speech recognition
search
Interest analysis
out remote diagnosis and treatment .It will help improve the relationship between doctors and patients and alleviate the problem of insufficient quality medical resources.
大数据英语幻灯片
The early years of data revoallenges
Data
privacy access and sharing
Analysis
“what is the data really telling us?”
summarizing the data interpreting defining and detecting anomalies
Big data
Taobao search
definition
definition
Big data is the need for new processing mode to have a stronger decision-making power, insight into the ability to find and process optimization to adapt to the massive, high growth rate and diversification of information assets.
fig. New types of research data about human behavior and society pose many opportunities if crucial infrastructural challenges are tackled.
Part 5 conclusion
Part 5 conclusion
Today data require scientific and computational intelligence. Big Data Future is a free, public, multidisciplinary conference on
大数据英语PPT演示课件
The early years of data revolution:
challenges
challenges
Data
privacy access and sharing
Analysis
“what is the data really telling us?”
summarizing the data interpreting defining and detecting anomalties
Data revolution
today a massive amount of data is regularly being generated and flowing from various sources, through different channels, every minute in today’s Digital Age.
fig. New types of research data about human behavior and society pose many opportunities if crucial infrastructural challenges are tackled.
Part 5 conclusion
Characteristics:
Volume : data size Velocity :speed of change Variety : different forms of data sources
application
application
Bank transactions
1.3 million transactions in 2015 worldwide;
《大数据专业英语》课件—12Data Security
个性化互动 购物体验 数据井 网络罪犯 只是…的问题 设立，安上 留神，谨防，提防 风险管理，风险管控 在许多方面 安全威胁
Phrases
dynamic data static data storage medium computational security access control method granular access control mandatory access control security flaw keep in mind
参考译文
2.10数据存储的隐私保护 NoSQL等数据存储存在许多安全漏洞，这些漏洞会导致隐私威胁。一个突出的安 全漏洞是，在标记或记录数据期间或在流式传输或收集数据时，无法加密数据； 把数据分发到不同的组的时候，也无法加密数据。
3.结论 组织必须确保所有大数据库都免受安全威胁和漏洞的影响。在数据收集期间，应 实现所有必要的安全保护，例如实时管理。考虑到大数据的庞大规模，组织应该 记住管理此类数据可能很困难并需要非常努力。但是，采取所有这些步骤将有助 于维护消费者隐私。
v.自动分级
n.验证，确认 n.过滤；筛选 adj.可信的，可靠的；认证了的 adj.合法的，合理的；正规的
n.预防；阻止，制止 n.映射器；映射程序 adj.智能的；聪明的；有智力的 adj.易受攻击的 n.来源，起源，出处 n.身份验证；认证；证明，鉴定 v.辨认，识别，承认
New Words
参考译文
2.大数据安全和隐私的挑战 大数据无法仅根据其规模来描述。但是，最基本的理解是，大数据是无法以传统数 据库方式处理其大小的数据集。这种数据积累有助于以多种方式改善客户服务。但 是，如此庞大的数据也会带来许多隐私问题，使大数据安全成为任何组织的主要关 注点。在数据安全和隐私领域，许多组织正在承认这些威胁的存在，并采取措施防 止这些威胁。
《大数据专业英语》课件—04ETL
参考译文
2.3 用于Hadoop的ETL——以及更多 ETL已经发展到支持集成，而不仅仅是传统的数据仓库。高级ETL工具可以 将结构化和非结构化数据加载并转换到Hadoop中。这些工具从Hadoop并行 读取和写入多个文件，简化了数据合并到公共转换过程。一些解决方案包含 针对在Hadoop上运行的事务和交互数据的预构建ETL转换库。ETL还可以与 跨事务系统、运营数据存储、BI平台、主数据管理（MDM）中心和云相集 成。
参考译文
2.5 ETL和数据质量 ETL和其它数据集成软件工具——用于数据清理、分析和审计——确保数据 值得信赖。 ETL工具能与数据质量工具集成，ETL供应商在其解决方案中包 含了相关工具（例如用于数据映射和数据沿袭的工具）。
2.6 ETL和元数据 元数据有助于我们了解数据的沿袭（来自何处）及其对组织中其它数据资产 的影响。随着数据架构变得越来越复杂，跟踪组织中不同数据元素的使用和 相关性非常重要。例如，如果将Twitter帐户名添加到客户数据库，则需要会 对哪些有影响，例如对ETL作业、应用程序或报告的影响。
3.5 ETL与ELT 先有ETL。后来，组织增加了ELT，它作为一种补充方法。ELT从源系统中提取数 据，将其加载到目标系统，然后使用源系统的处理能力进行转换。这加速了数据 处理，因为它发生在数据所在之处。
参考译文
3.6数据质量 在集成数据之前，通常会创建一个临时区域，可以清理数据，数据值可以标准化 （NC和North Carolina，Mister和Mr.，或Matt和Matthew），可以验证地址并删 除重复项。许多解决方案仍然是独立的，但数据质量程序现在可以作为数据集成 过程中的转换的一部分来运行。
vt.混合；（使）调和；协调 n.混合；混合物
《大数据专业英语》课件—08Data Processing
adj.预定义的 n.沉淀物 v.沉淀 v.连接；联结
vt.调查；审查；研究 vi.作调查
Phrases
data pre-processing garbage in, garbage out data gathering missing value computational biology knowledge discovery training set survey data be split into macro editing aggregation method
[ɪˈreləvənt] [ˈnɔɪzɪ]
unreliable preparation filter considerable
[ˌʌnrɪˈlaɪəbl] [ˌprepəˈreɪʃn] [ˈfɪltə] [kənˈsɪdərəbl]
selection transformation extraction perform manually assistance
参考译文
2.1.3宏编辑 宏编辑有两种方法： •聚合方法 在发布之前，几乎每个统计机构都遵循这种方法：验证要公布的数字是否合理。这 是通过将发布表中的数量与先前发布的相同数量进行比较来实现。如果观察到异常 值，则对导致可疑数量的各个记录和字段应用宏编辑程序。 •分布方法 可用数据用于表征变量的分布。然后将所有单个值与分布进行比较。包含可能被视 为不常见的值（给定分布）的记录是进一步检查和可能编辑的候选者。
参考译文
4.1典型用途 数据转换通常应用于数据集内的不同实体（例如，字段、行、列、数据值 等），并且可以包括诸如提取、解析、加入、标准化、扩充、清理、合并 和过滤操作。期望整理后的数据可供下游使用。 接收整理结果数据的可以是个人，例如将进一步调查数据的数据架构师或 数据科学家、将直接在报告中使用数据的业务用户或者进一步处理数据并 将其写入目标（如数据仓库、数据湖或下游应用程序）的系统。