Ⅰ 大数据时代，对于我们普通人来说，有什么好处
就业机会变多，眼界可以更开阔。大数据时代，需要的人才越来越多，对年轻人而言就业变得容易了。大数据时代也可以让人的眼界更开阔，毕竟网络上什么都查得到。
Ⅱ 对数字商业的看法120字英语作文
数字商务（Digital Commerce）是指利用互联网、物联网、无线通信等通信技术和数据分析手段将商务的流程、渠道、营销、运营等流程数字化、互联网化、智能化。
同电子商务不同的是，数字商务不仅仅是将现代信息技术和商务的结合，而是集中于将数据的价值应用到商业中去，将商业的流程和业务智能化，有机化。
各大城市也在推行数字商务的发展，建立各种机制和提供优惠政策来促进数字商务的发展。比如说上海嘉定新城，依托江浙沪一带的商务优势和信息化基础，在产业升级的过程中将促进数字商务的发展作为重要发展战略。
数字化转型对中国企业而言，不仅是一道战略选择题，更是一道生存题。
有这样一种说法:农业文明3000年，中国领先了2000多年的历史；工业文明300年，中国落后了150年甚至200年的历史；智能文明60年，中国与世界基本同步。也就是说，在工业文明时期，中国企业输在了起跑线上。但是在数字化、智能文明时代，中国企业如果能够抓住数字化智能文明时代的历史性发展机遇，中国企业不仅能够跟欧美企业同步，甚至可以变道超车。
在过去10年里，美国几乎所有的行业都数字化了。从会计到仓储，从人事到日程安排，数字技术无处不在，通过这种数字化进程，美国的企业也尝到了甜头。据IDG（美国国际数据集团）研究报告：全球1000大企业中67％已将数字化转型变成企业级战略。企业数字化转型也正成为许多中国企业的核心战略。
中国已将大数据上升为国家战略，但研究显示：过去，中国的互联网发展以消费者为主带动、而不是企业为导向。中国消费者网络零售消费占比为7%-8%，已超过美国的6%；而在企业云服务渗透率方面中国比率为21%，远低于美国的55%-63%；中小企业运营中互联网使用率为20%-25%，而美国同一数据则是72%-85%。
Ⅲ 跪求写一篇数据科学与大数据技术对社会的 贡献的英语作文，不少于200字。急用急用。
这个从社会的发展角度分析数据科学与大数据对人民生活的影响，以及重要性，说明人们生活越来越离不开数据，应该积极面对社会的发展和进步。
Ⅳ 大数据的优势在哪里
现在的社会是一个高速发展的社会，科技发达，信息流通，人们之间的交流越来越密切，生活也越来越方便，大数据就是这个高科技时代的产物。大数据”是指以多元形式，自许多来源搜集而来的庞大数据组，往往具有实时性。在企业对企业销售的情况下，这些数据可能得自社交网络、电子商务网站、顾客来访纪录，还有许多其他来源。
目前大数据几乎每个企业都在使用，大数据分析提供了一个真正具有潜在利益的矿藏，但它也带来了可能抵消潜在收益的重大挑战。
• 更精准的决策 ：在NewVantage Partners公司调查中，36.2%的受访者表示更好的决策是他们大数据分析工作的首要目标。此外，84.1%的受访者表示已开始朝着这一目标努力，59.0%的受访者表示取得了一些可衡量的成功，其总体成功率为69.0%。大数据分析可以为业务决策者提供他们所需的数据驱动的洞察力，以帮助企业开展竞争和业务发展。
• 提高生产力 ：来自供应商Syncsort公司的另一项调查发现，59.9%的受访者使用Hadoop和Spark等大数据工具来提高业务的工作效率。现代大数据工具使分析师能够更快地分析更多数据，从而提高个人生产力。此外，从这些分析中获得的见解通常使组织能够在整个公司内更广泛地提高生产力。
• 降低成本 ：Syncsort公司和NewVantage公司的调查均发现大数据分析正在帮助企业降低成本。近五分之三(59.4%)的受访者表示Syncsort公司的大数据工具帮助他们提高了运营效率，并降低了成本，NewVantage公司的调查中，约三分之二(66.7%)的受访者表示他们已开始使用大数据来降低成本。然而有趣的是，只有13.0%的受访者选择降低成本作为大数据分析的主要目标，这表明对于许多人而言，这只是一个非常受欢迎的附带好处。
• 改善客户服务 ：在NewVantage公司调查的受访者中，改善客户服务是大数据分析项目的第二个最常见的主要目标，53.4%的受访者表示在这方面取得了一些成功。社交媒体、客户关系管理(CRM)系统、其他客户为当今的企业提供了大量有关其客户的信息，他们很自然地会使用这些数据来更好地为这些客户提供服务。
• 欺诈检测 ：大数据分析的另一个常见用途用于欺诈检测，特别是在金融服务行业。依赖于机器学习的大数据分析系统的一大优势是它们在检测模式和异常方面非常出色。这些能力可以让银行和信用卡公司能够发现被盗信用卡或欺诈性购买，并且通常是在持卡人知道出现问题之前发现问题。
• 增加收入 ：当组织使用大数据来改善决策并改善客户服务时，增加收入通常是一个自然的结果。在Syncsort公司的调查中，超过一半的受访者(54.7%)表示他们正在使用大数据工具来增加收入，并根据更好的洞察力加速增长。
• 提高灵活性 ：同样，从Syncsort公司的调查报告中，41.7%的受访者表示大数据的好处之一是能够提高业务/IT敏捷性。许多组织正在使用其大数据来更好地调整其IT和业务工作，并且他们正在使用他们的分析来支持更快、更频繁地更改其业务战略和策略。
• 更好的创新 ：创新是大数据的另一个共同利益，NewVantage公司的调查发现，11.6%的高管正在投资分析，主要是作为创新和颠覆市场的手段。他们认为，如果他们能够收集竞争对手所没有的见解，他们就可以通过新产品和服务领先于其他企业。
• 上市速度 ：在这些方面，很多企业表示将使用大数据来加快产品上市速度。只有8.8%的受访者表示这是大数据的首要目标，但53.6%受访者已经开始朝着这个目标努力，其中54.1%的受访者表示取得了一些成功。大数据的这种优势也可能带来额外的好处，例如更快的增长和更高的收入。
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Ⅳ 关于贵阳大数据的高中英语作文
相信自己
之所以成功来之不易，是因为用汗水堆积成的堡垒；之所以未来明灯常亮，是因为用坚持叠成的灯塔；之所以人生绚烂多姿，是因为用努力筑成的丰碑。因为相信自己，所以坚持不懈；因为相信自己，所以勇往直前。扬起自信的风帆，成功仅一步之遥。
曾经遇事胆怯的我，连与他人沟通都会害怕。直到有一次，我和另两位同学代表班级去参加辩论赛，小组成员个个都对答如流，尽管自己心里很着急，但依旧没有勇气站起来辩论。对于我的一大考验摆在面前。因为心里希望自己能成功，希望自己能为班级做出贡献，希望自己所在的小组能获奖，在经过一番思想斗争后，我还是站了起来，反对对方的观点，说完之后，我赢得了属于我自己的掌声，我的内心十分欣喜。第一次，我有勇气挑战了自己；第一次，我不再胆怯；第一次，我也获得了深深的鼓励;我相信自己，我对自己说：“我能行！”
其实无论做什么事，如何去做。都必须县相信自己，别人才会更相信你，因为相信了自己，才会有信心一直做下去，才会学的自我欣赏，才会学有所成。不要害怕困难，也不要害怕自己不行，因为不试又怎么知道？不经历风雨有怎能见彩虹？相信自己就是塑造未来。
伴着盛开的花，蝴蝶才能快乐地飞舞；带着希望，梦想才能飞往高处；迎着温暖的风，我们不再感到孤独。用自己的实力来证明自己，不停下追逐快乐的脚步，不停下追赶幸福的步伐，最后获得最勇敢的幸福，只因相信自己，一直相信自己。也未曾说过放弃。
所以，相信自己，用自己的双手去创造一个属于自己的天堂。卸下重负，张开双翼，自由的翱翔于天边。
请，相信自己，扬起自信的风帆，驶向成功的彼岸！
Ⅵ 求一篇与大数据或者大数据信息安全专业相关的原版英文文献及其翻译,3000字左右。好人，拜托！
Big data refers to the huge volume of data that cannot
be stored and processed with in a time frame in
traditional file system.
The next question comes in mind is how big this data
needs to be in order to classify as a big data. There is a
lot of misconception in referring a term big data. We
usually refer a data to be big if its size is in gigabyte,
terabyte, Petabyte or Exabyte or anything larger than
this size. This does not define a big data completely.
Even a small amount of file can be referred to as a big
data depending upon the content is being used.
Let’s just take an example to make it clear. If we attach
a 100 MB file to an email, we cannot be able to do so.
As a email does not support an attachment of this size.
Therefore with respect to an email, this 100mb file
can be referred to as a big data. Similarly if we want to
process 1 TB of data in a given time frame, we cannot
do this with a traditional system since the resource
with it is not sufficient to accomplish this task.
As you are aware of various social sites such as
Facebook, twitter, Google+, LinkedIn or YouTube
contains data in huge amount. But as the users are
growing on these social sites, the storing and processing
the enormous data is becoming a challenging task.
Storing this data is important for various firms to
generate huge revenue which is not possible with a
traditional file system. Here is what Hadoop comes in
the existence.
Big Data simply means that huge amount
of structured, unstructured and semi-structured
data that has the ability to be processed for information. Now a days massive amount of data
proced because of growth in technology,
digitalization and by a variety of sources, including
business application transactions, videos, picture ,
electronic mails, social media, and so on. So to process
these data the big data concept is introced.
Structured data: a data that does have a proper format
associated to it known as structured data. For example
the data stored in database files or data stored in excel
sheets.
Semi-Structured Data: A data that does not have a
proper format associated to it known as structured data.
For example the data stored in mail files or in docx.
files.
Unstructured data: a data that does not have any format
associated to it known as structured data. For example
an image files, audio files and video files.
Big data is categorized into 3 v’s associated with it that
are as follows:[1]
Volume: It is the amount of data to be generated i.e.
in a huge quantity.
Velocity: It is the speed at which the data getting
generated.
Variety: It refers to the different kind data which is
generated.
A. Challenges Faced by Big Data
There are two main challenges faced by big data [2]
i. How to store and manage huge volume of data
efficiently.
ii. How do we process and extract valuable
information from huge volume data within a given
time frame.
These main challenges lead to the development of
hadoop framework.
Hadoop is an open source framework developed by
ck cutting in 2006 and managed by the apache
software foundation. Hadoop was named after yellow
toy elephant.
Hadoop was designed to store and process data
efficiently. Hadoop framework comprises of two main
components that are:
i. HDFS: It stands for Hadoop distributed file
system which takes care of storage of data within
hadoop cluster.
ii. MAPREDUCE: it takes care of a processing of a
data that is present in the HDFS.
Now let’s just have a look on Hadoop cluster:
Here in this there are two nodes that are Master Node
and slave node.
Master node is responsible for Name node and Job
Tracker demon. Here node is technical term used to
denote machine present in the cluster and demon is
the technical term used to show the background
processes running on a Linux machine.
The slave node on the other hand is responsible for
running the data node and the task tracker demons.
The name node and data node are responsible for
storing and managing the data and commonly referred
to as storage node. Whereas the job tracker and task
tracker is responsible for processing and computing a
data and commonly known as Compute node.
Normally the name node and job tracker runs on a
single machine whereas a data node and task tracker
runs on different machines.
B. Features Of Hadoop:[3]
i. Cost effective system: It does not require any
special hardware. It simply can be implemented
in a common machine technically known as
commodity hardware.
ii. Large cluster of nodes: A hadoop system can
support a large number of nodes which provides
a huge storage and processing system.
iii. Parallel processing: a hadoop cluster provide the
accessibility to access and manage data parallel
which saves a lot of time.
iv. Distributed data: it takes care of splinting and
distributing of data across all nodes within a cluster
.it also replicates the data over the entire cluster.
v. Automatic failover management: once and AFM
is configured on a cluster, the admin needs not to
worry about the failed machine. Hadoop replicates
the configuration Here one of each data iscopied or replicated to the node in the same rack
and the hadoop take care of the internetworking
between two racks.
vi. Data locality optimization: This is the most
powerful thing of hadoop which make it the most
efficient feature. Here if a person requests for a
huge data which relies in some other place, the
machine will sends the code of that data and then
other person compiles it and use it in particular
as it saves a log to bandwidth
vii. Heterogeneous cluster: node or machine can be
of different vendor and can be working on
different flavor of operating systems.
viii. Scalability: in hadoop adding a machine or
removing a machine does not effect on a cluster.
Even the adding or removing the component of
machine does not.
C. Hadoop Architecture
Hadoop comprises of two components
i. HDFS
ii. MAPREDUCE
Hadoop distributes big data in several chunks and store
data in several nodes within a cluster which
significantly reces the time.
Hadoop replicates each part of data into each machine
that are present within the cluster.
The no. of copies replicated depends on the replication
factor. By default the replication factor is 3. Therefore
in this case there are 3 copies to each data on 3 different
machines。
reference:Mahajan, P., Gaba, G., & Chauhan, N. S. (2016). Big Data Security. IITM Journal of Management and IT, 7(1), 89-94.
自己拿去翻译网站翻吧，不懂可以问
Ⅶ 随着大数据时代英文
摘要：As the big data era, all kinds of data in the society is growing at a rapid speed, the library also inevitably faced with the impact of the wave data information. This paper analyses the characteristics of data, data source library management, focusing on the large data will be brought about by the challenge, the final analysis of the times books management development direction of large data. Mainly includes the influence on library management of large data: data of complex data processing test library computing power, data analysis to the mining depth of traditional requirements for Library Infrastructure challenges and big data era. Future library management from the exploratory data analysis tools and technology, attach importance to the construction of infrastructure and data collection, improving several books management intelligent degree of development. Keywords large structured data and unstructured Library
Ⅷ 英语作文大数据和我们的生活
First,I think my life is healthy.I'm allowed to play computer games every day.So I could be relaxed myself.Then,I go to school on foot,beacuse it isn't far from my home.I am healthy.I also paly football after school.Finally,I sleep eight hours every night.I get up early.I often have a quick breakfast,and take a shower.
In a word,I think it's necessary for us to keep in a good health.
Ⅸ "大数据"怎样用英文表述呢
大数据的英文翻译是big data。
释义：大数据；巨量资料；海量资料；海量数据
big block data称为大区块资料 ; 大区块资料
Big Bang Data数据大爆炸
Big Earth Data地球大数据
Big Brain Data大脑巨量资料
Big Complex Data大型复杂数据
1、?
大数据将如何改变您的做事方式？
2、.
但是庞大数据还会产生远比这更为严重的后果。
3、 themselves.
在庞大数据的世界中，相关数据几乎是自行浮出水面。
4、Ifyourservicedeals withbigdata,that's howthey'rerelated.
如果你的服务要处理大数据，那正是它们相关的东西。
5、Whatis therelationshiptoSOA?Related tothisisBigData, how isitrelatedtoSOA?
它与SOA之间有什么关系吗？与之关联的是大数据，那么它又是怎样和SOA关联起来的呢？