关于大数据时代的论文英文翻译怎么写
bigdata指规模巨大且复杂，用现有的数据处理工具（on-handdatabasemanagementtools）难以获取（capture）、整理（curate）、管理（manage）以及处理（process）的数据信息统称。大数据的特点可以总结为4V：volume（大量）、velocity（高速）、variety（多变）、veracity（准确）。
大数据时代英语是 big data era
大数据时代时代_有道翻译翻译结果：The era of big data era
关于大数据时代的论文英文翻译
大数据时代英语翻译：The era of big data era
The challenges and countermeasures for enterprise information systems in the era of big
Big data refers to the huge volume of data that cannotbe stored and processed with in a time frame intraditional file The next question comes in mind is how big this dataneeds to be in order to classify as a big There is alot of misconception in referring a term big Weusually refer a data to be big if its size is in gigabyte，terabyte， Petabyte or Exabyte or anything larger thanthis This does not define a big data Even a small amount of file can be referred to as a bigdata depending upon the content is being Let’s just take an example to make it If we attacha 100 MB file to an email， we cannot be able to do As a email does not support an attachment of this Therefore with respect to an email， this 100mb filecan be referred to as a big Similarly if we want toprocess 1 TB of data in a given time frame， we cannotdo this with a traditional system since the resourcewith it is not sufficient to accomplish this As you are aware of various social sites such asFacebook， twitter， Google+， LinkedIn or YouTubecontains data in huge But as the users aregrowing on these social sites， the storing and processingthe enormous data is becoming a challenging Storing this data is important for various firms togenerate huge revenue which is not possible with atraditional file Here is what Hadoop comes inthe Big Data simply means that huge amountof structured， unstructured and semi-structureddata that has the ability to be processed for Now a days massive amount of dataproduced because of growth in technology，digitalization and by a variety of sources， includingbusiness application transactions， videos， picture ，electronic mails， social media， and so So to processthese data the big data concept is Structured data: a data that does have a proper formatassociated to it known as structured For examplethe data stored in database files or data stored in Semi-Structured Data: A data that does not have aproper format associated to it known as structured For example the data stored in mail files or in Unstructured data: a data that does not have any formatassociated to it known as structured For examplean image files， audio files and video Big data is categorized into 3 v’s associated with it thatare as follows:[1]Volume: It is the amount of data to be generated in a huge Velocity: It is the speed at which the data Variety: It refers to the different kind data which A Challenges Faced by Big DataThere are two main challenges faced by big data [2] How to store and manage huge volume of How do we process and extract valuableinformation from huge volume data within a giventime These main challenges lead to the development ofhadoop Hadoop is an open source framework developed byduck cutting in 2006 and managed by the apachesoftware Hadoop was named after yellowtoy Hadoop was designed to store and process Hadoop framework comprises of two maincomponents that are: HDFS: It stands for Hadoop distributed filesystem which takes care of storage of data withinhadoop MAPREDUCE: it takes care of a processing of adata that is present in the HDFSNow let’s just have a look on Hadoop cluster:Here in this there are two nodes that are Master Nodeand slave Master node is responsible for Name node and JobTracker Here node is technical term used todenote machine present in the cluster and demon isthe technical term used to show the backgroundprocesses running on a Linux The slave node on the other hand is responsible forrunning the data node and the task tracker The name node and data node are responsible forstoring and managing the data and commonly referredto as storage Whereas the job tracker and tasktracker is responsible for processing and computing adata and commonly known as Compute Normally the name node and job tracker runs on asingle machine whereas a data node and task trackerruns on different B Features Of Hadoop:[3] Cost effective system: It does not require anyspecial It simply can be implementedin a common machine technically known ascommodity Large cluster of nodes: A hadoop system cansupport a large number of nodes which providesa huge storage and processing Parallel processing: a hadoop cluster provide theaccessibility to access and manage data parallelwhich saves a lot of Distributed data: it takes care of splinting anddistributing of data across all nodes within a it also replicates the data over the entire Automatic failover management: once and AFMis configured on a cluster， the admin needs not toworry about the failed Hadoop replicatesthe configuration Here one copy of each data iscopied or replicated to the node in the same rackand the hadoop take care of the internetworkingbetween two Data locality optimization: This is the mostpowerful thing of hadoop which make it the mostefficient Here if a person requests for ahuge data which relies in some other place， themachine will sends the code of that data and thenother person compiles it and use it in particularas it saves a log to Heterogeneous cluster: node or machine can beof different vendor and can be working ondifferent flavor of operating Scalability: in hadoop adding a machine orremoving a machine does not effect on a Even the adding or removing the component ofmachine does C Hadoop ArchitectureHadoop comprises of two HDFS MAPREDUCEHadoop distributes big data in several chunks and storedata in several nodes within a cluster whichsignificantly reduces the Hadoop replicates each part of data into each machinethat are present within the The of copies replicated depends on the By default the replication factor is Thereforein this case there are 3 copies to each data on 3 differentmachines。reference:Mahajan， P， Gaba， G， & Chauhan， N S (2016) Big Data S IITM Journal of Management and IT， 7(1)， 89-自己拿去翻译网站翻吧，不懂可以问
大数据时代英语是 big data era
关于大数据时代的论文英文翻译版
大数据时代英语翻译：The era of big data era
Big data refers to the huge volume of data that cannotbe stored and processed with in a time frame intraditional file The next question comes in mind is how big this dataneeds to be in order to classify as a big There is alot of misconception in referring a term big Weusually refer a data to be big if its size is in gigabyte，terabyte， Petabyte or Exabyte or anything larger thanthis This does not define a big data Even a small amount of file can be referred to as a bigdata depending upon the content is being Let’s just take an example to make it If we attacha 100 MB file to an email， we cannot be able to do As a email does not support an attachment of this Therefore with respect to an email， this 100mb filecan be referred to as a big Similarly if we want toprocess 1 TB of data in a given time frame， we cannotdo this with a traditional system since the resourcewith it is not sufficient to accomplish this As you are aware of various social sites such asFacebook， twitter， Google+， LinkedIn or YouTubecontains data in huge But as the users aregrowing on these social sites， the storing and processingthe enormous data is becoming a challenging Storing this data is important for various firms togenerate huge revenue which is not possible with atraditional file Here is what Hadoop comes inthe Big Data simply means that huge amountof structured， unstructured and semi-structureddata that has the ability to be processed for Now a days massive amount of dataproduced because of growth in technology，digitalization and by a variety of sources， includingbusiness application transactions， videos， picture ，electronic mails， social media， and so So to processthese data the big data concept is Structured data: a data that does have a proper formatassociated to it known as structured For examplethe data stored in database files or data stored in Semi-Structured Data: A data that does not have aproper format associated to it known as structured For example the data stored in mail files or in Unstructured data: a data that does not have any formatassociated to it known as structured For examplean image files， audio files and video Big data is categorized into 3 v’s associated with it thatare as follows:[1]Volume: It is the amount of data to be generated in a huge Velocity: It is the speed at which the data Variety: It refers to the different kind data which A Challenges Faced by Big DataThere are two main challenges faced by big data [2] How to store and manage huge volume of How do we process and extract valuableinformation from huge volume data within a giventime These main challenges lead to the development ofhadoop Hadoop is an open source framework developed byduck cutting in 2006 and managed by the apachesoftware Hadoop was named after yellowtoy Hadoop was designed to store and process Hadoop framework comprises of two maincomponents that are: HDFS: It stands for Hadoop distributed filesystem which takes care of storage of data withinhadoop MAPREDUCE: it takes care of a processing of adata that is present in the HDFSNow let’s just have a look on Hadoop cluster:Here in this there are two nodes that are Master Nodeand slave Master node is responsible for Name node and JobTracker Here node is technical term used todenote machine present in the cluster and demon isthe technical term used to show the backgroundprocesses running on a Linux The slave node on the other hand is responsible forrunning the data node and the task tracker The name node and data node are responsible forstoring and managing the data and commonly referredto as storage Whereas the job tracker and tasktracker is responsible for processing and computing adata and commonly known as Compute Normally the name node and job tracker runs on asingle machine whereas a data node and task trackerruns on different B Features Of Hadoop:[3] Cost effective system: It does not require anyspecial It simply can be implementedin a common machine technically known ascommodity Large cluster of nodes: A hadoop system cansupport a large number of nodes which providesa huge storage and processing Parallel processing: a hadoop cluster provide theaccessibility to access and manage data parallelwhich saves a lot of Distributed data: it takes care of splinting anddistributing of data across all nodes within a it also replicates the data over the entire Automatic failover management: once and AFMis configured on a cluster， the admin needs not toworry about the failed Hadoop replicatesthe configuration Here one copy of each data iscopied or replicated to the node in the same rackand the hadoop take care of the internetworkingbetween two Data locality optimization: This is the mostpowerful thing of hadoop which make it the mostefficient Here if a person requests for ahuge data which relies in some other place， themachine will sends the code of that data and thenother person compiles it and use it in particularas it saves a log to Heterogeneous cluster: node or machine can beof different vendor and can be working ondifferent flavor of operating Scalability: in hadoop adding a machine orremoving a machine does not effect on a Even the adding or removing the component ofmachine does C Hadoop ArchitectureHadoop comprises of two HDFS MAPREDUCEHadoop distributes big data in several chunks and storedata in several nodes within a cluster whichsignificantly reduces the Hadoop replicates each part of data into each machinethat are present within the The of copies replicated depends on the By default the replication factor is Thereforein this case there are 3 copies to each data on 3 differentmachines。reference:Mahajan， P， Gaba， G， & Chauhan， N S (2016) Big Data S IITM Journal of Management and IT， 7(1)， 89-自己拿去翻译网站翻吧，不懂可以问
People who talk about big data often take Lin Biao as an Lin Biao recorded some detailed and unimportant data after a Such as seized guns， the proportion of rifles and pistols， the age levels of war prisoners， seized grain， whether they are sorghum or millet， ， all of which were unavoidably recorded in the Others laughed at But later， he determined where the enemy headquarters were according to these
大数据时代英语是 big data era
关于大数据时代的论文英文翻译初中
The challenges and countermeasures for enterprise information systems in the era of big
大数据时代The era of Big Data
People who talk about big data often take Lin Biao as an Lin Biao recorded some detailed and unimportant data after a Such as seized guns， the proportion of rifles and pistols， the age levels of war prisoners， seized grain， whether they are sorghum or millet， ， all of which were unavoidably recorded in the Others laughed at But later， he determined where the enemy headquarters were according to these
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关于大数据时代的论文摘要英文翻译
With the continuous development of digital industry， the electronic information industry rise abruptly， emerging origin is mature with each passing day， international competition is becoming more and more In recent years， the India， Vietnam and other developing countries take various preferential policies to foster its industrial development， those countries in the human cost than our country more competitive， how can we improve our country in the digital industry export competitiveness? According to the present Chinese electronic digital products exports in the current situation， music guest company digital speakers and other products in the future international trade strategy launches the research， through the market survey and needs analysis pointed out in its international trade development 望采纳！
大数据时代时代_有道翻译翻译结果：The era of big data era
大数据时代英语是 big data era
摘要：随着国际互联网的发展，以信息为内容的数字网络技术引发了高科技的崛起，同时也对现行的知识产权制度提出了严峻的挑战。 Abstract: with the international development of the Internet， based on the information content of digital network technology triggered a high-tech rise， simultaneously to current intellectual property system proposed severe 由于互联网的虚拟特性使人们对网络作品的定位、网络作品传播过程中涉及知识产权的认识产生了分歧，从而给传统的知识产权体系带来了无尽的侵权纠纷。 Thanks to the Internet virtual properties enabling people to network works localization， the process of transmission network works involving intellectual property understanding differences developed， thus to traditional intellectual property system brings endless infringement 本文从知识产权和网络知识产权的概念入手，通过分析网络知识产权保护的必要性，网络知识产权保护的现状，提出了关于网络知识产权保护的对策。 This article from the intellectual property rights and network knowledge the concept of property right， analyzing the necessity of network of intellectual property protection， the network of intellectual property protection situation， this paper proposes about network of intellectual property protection 关键词：知识产权 网络知识产权保护 保护对策 Keywords: intellectual property network protection of intellectual property protection countermeasures