by Jeff Desjardins
The sun never sets on the creation of new data.
新的数据好比长江东逝水，永不止步，滚滚而来。
Yes, the rate of generation may slow down at night as people send fewer emails and watch fewer videos. But for every person hitting the hay, there is another person on the opposite side of the world that is turning their smartphone on for the day.
是的，新数据产生的速率到了夜间也许会出现下降，因为人们晚上发邮件、看视频的数量会变少。但对于每一个上床j就寝的人来说，在地球的另一端另一个人却正在打开智能手机。
As a result, the scale of data being generated—even when we look at it through a limited lens of one minute at a time—is quite mind-boggling to behold.
因此，即使只用1分钟这一微小的时间单位来计量，新数据爆发的规模也足以令人感到惊叹。
通过数据诞生的源头来看大数据的爆发式增长
Today’s infographic comes to us from Domo, and it shows the amount of new data generated each minute through several different platforms and technologies.
今天的这张信息图表来自Domo网站，该图显示的是每一分钟通过几个不同的平台和科技手段所诞生的新数据的规模。
Let’s start by looking at what happens every minutefrom a broad perspective:
先从更广泛的视角了解一下每分钟都会发生什么：
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Americans use 4,416,720 GB of internet data
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美国人每分钟使用的互联网数据总量为4,416,720GB；
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There are 188,000,000 emails sent
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美国人每分钟发出188,000,000个邮件；
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There are 18,100,000 texts sent
美国人每分钟发出18,100,000个短信；
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There are 390,030 apps downloaded
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美国人每分钟下载390,030个手机应用程序。
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Now lets look at platform-specific data on a per minutebasis:
下面再来看看各个具体的应用平台每分钟产生新数据的情况：
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Giphy serves up 4,800,000 gifs
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在Giphy（在线动态GIF图片搜索引擎）上每分钟进行的图片搜索次数为4,800,000；
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Netflix users stream 694,444 hours of video
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奈飞网站用户每分钟浏览的视频时长为694,444小时；
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Instagram users post 277,777 stories
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图片分享应用网站Instagram的用户每分钟贴出277,777个故事；
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Youtube users watch 4,500,000 videos
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Youtube用户每分钟在线浏览的视频数量为4,500,000；
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Twitter users send 511,200 tweets
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推特用户每分钟发出511,200个推文；
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Skype users make 231,840 calls
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Skype用户每分钟进行231,840次网络通话；
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Airbnb books 1,389 reservations
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爱彼迎的用户每分钟进行1,389次房屋预定；
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Uber users take 9,772 rides
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优步用户每分钟打车9,772次；
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Tinder users swipe 1,400,000 times
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手机交友应用程序Tinder的用户每分钟进行1,400,000次交友配对；
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Google conducts 4,497,420 searches
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谷歌网站上每分钟搜索次数为4,497,420；
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Twitch users view 1,000,000 videos
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游戏直播平台的用户每分钟浏览的视频次数为1,000,000。
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Imagine being given the task to build a server infrastructure capable of handling any of the above items. It’s a level of scale that’s hard to comprehend.
试想如果有谁被安排一项任务构建一个具有以上信息处理能力的服务器架构，这工作的难度可是够大的。
Also, imagine how difficult it is to make sense of this swath of data. How does one even process insights from the many billions of Youtube videos watched per day?
此外，还请设想一下搞懂如此巨大数据流量的难度有多大，谁能想象视频网站上每天阅览的次数竟然多达数十亿次？
为啥大数据会变得更“大”？
The above statistics are already mind-bending, but consider that the global total of internet users is still growing at roughly a 9% clip. This means the current rate of data creation is still just scratching the surface of its ultimate potential.
以上的统计数据已经让人感到怀疑人生了，但请各位想想全球互联网用户总数仍在以9%的速度快速增长，这就意味着与其终极潜能相比，当前数据产生的速率只是九牛一毛。
In fact, as We Are Social’s recent report on internet usage reveals, a staggering 367 million new internet users were added in between January 2018 and January 2019:
实际上根据互联网调查机构WE ARE SOCIAL近期发布的关于互联网应用的报告显示，在2018年1月至2019年1月期间新增加的全球互联网用户总数竟然多达3.67亿。
Global internet penetration sits at 57% in 2019, meaning that billions of more people are going to be using the above same services—including many others that don’t even exist yet.
全球互联网的渗透率在2019年达到57%，意味着有数十亿人将在未来享有以上提到的互联网服务，甚至还将享有很多今天尚未出现的服务。
Combine this with more time spent on the internet per user and technologies like 5G, and we are only at the beginning of the big data era.
此外，再考虑到每个互联网用户在网上所花的时间将越来越多以及未来的科技如5G将得到大规模的应用，就知道在我们的眼前大数据时代的帷幕才刚刚拉开。
