用户分析英文

Analyst(分析员)职位一般来说适合刚从大学院校毕业或刚攻读完高等学位但缺乏工作经验的应聘者。作为新聘分析员，你将更多地了解公司业务，建立重要的人际关系，并培养晋升至更高职位所需的各种技能。 Associate(经理)一般需要二到五年的工作经验或者拥有高级学位（如工商管理硕士），或者两者兼有。作为新聘经理，你将成为公司业务的重要组成部分，并可迅速承担产品或客户责任。

数据分析是指用适当的统计分析 方法 对收集来的大量数据进行分析，那么你知道数据分析用英语怎么说吗? 下面和我一起来学习一下数据分析的英语说法吧。

data analysis

数据分析员 Data Analyst

矩阵数据分析法 Matrix Data Analysis

统计数据分析 statistical data analysis

数据分析设备 data analysis facilities

经济与数据分析 Economic and Statistical Analysis

1. Basic to any analysis of categorical data is a consideration of how the data was collected.

任何范畴数据分析的基础在于考虑数据是怎样收集的.

2. Data were analyzed using variance and multiple regression analysis.

数据分析采用方差分析、多元回归分析.

3. Hypotheses testing and general data analysis are accomplished with regression analysis.

数据分析过程主要运用回归分析完成.

4. Let me make this clear: A bar chart is not analytics.

首先我们必须明白: 一张条形图不是数据分析.

5. Good skills of data analysis and reporting by computer.

熟练运用办公自动化进行数据分析和 报告 .

6. Responsible for temperature monitoring devices management and temperature excursion mation.

负责温度追踪仪器的治理及超标温度数据分析.

7. Good ability at test design and operating, data analysis and summary.

能独立进行测试计划设计,测试操作, 及进行数据分析汇总.

8. In data analysis, congregate is a process of large amount original data.

汇总被广泛应用于数据分析, 是一种对原始数据进行统计加工整理的过程.

9. In chapter 6, the results of experiments and data analysis are provided.

第六章给出了该系统在正式测试中的结果以及数据分析.

10. SPM 99 was used to process data and localize functional areas.

采用SPM99软件进行数据分析和脑功能区定位.

11. Provide HR information analysis report and track the progress.

提交人力资源数据分析报告并督导执行.

12. VDA dynamically identifies different protocol segments in a packet.

垂直数据分析(VDA)动态识别一个包中不同的协议段.

13. The original analysis detected storm - driven swell shaking the ice.

通过最初的数据分析发现,猛烈的膨胀会对冰产生动摇作用.

14. Providing daily operational analysis report to relevant personals and project managers.

为项目负责人及相关人员提供日常运营数据分析报告.

15. The reliability life data analysis is an important basis of reliability engineering.

可靠性寿命数据分析是可靠性工程研究的重要基础.

Clay Christensen tells a good joke about a tour of heaven.

克雷.克里斯坦森(Clay Christensen)讲了一个有关天堂旅游的有趣笑话。

How come there’s no data here? the Harvard professor asks his celestial guide.

这里怎么没有数据呢?这位哈佛教授问他的天堂向导。

Because data lies, comes the response.

因为数据撒谎，对方回答说。

And that is why, Prof Christensen goes on, whenever anyone says ‘Show me the data’, I just say ‘Go to hell’.

克里斯坦森教授接着讲，所以每当有人说‘把数据拿给我看’时，我就会说‘下地狱去’。

The gag got a laugh at last week’s Drucker Forum in Vienna,

在近期在维也纳举行的德鲁克论坛(Drucker Forum)上，这个笑话引起了笑声。

where fans of the late Peter Drucker’s claim that management is a liberal art voiced fears about the way data are wielded to crush human insight and inventiveness.

在论坛上，认同已故彼得.德鲁克(Peter Drucker)的管理属于一门文科观点的粉丝们，表达了对数据被用来碾压人类洞察力和创造力的担心。

But there are signs of a backlash against big data even where it has loomed largest.

但目前有迹象表明，即便在大数据运用最广泛的领域，大数据也遭遇了强烈反弹。

As chief executive of UK supermarket chain J Sainsbury until 2014, Justin King commanded a data set that showed, for instance, that purchases of diet products were the best indication that customers were planning to go on holiday — and that they might therefore be open to some deft direct marketing of suntan lotion.

比如，担任英国连锁超市森宝利(J Sainsbury)首席执行官直至2014年的贾斯廷.金(Justin King)掌握的一个数据集显示，购买减肥食品是顾客打算去度假的最佳信号，因此他们可能很容易接受某些精明的防晒霜直接营销。

He believes retailers should use such information to represent the shopper better in, say, negotiations with suppliers.

他认为，零售商应当使用这类数据——比如在与供应商的谈判中——更好地代表顾客。

But at a Financial Times 125 Forum I chaired recently, he said he worried data were now used against customers.

但在不久前我主持的英国《金融时报》125论坛(FT 125 Forum)上，他表示，他担心如今数据的使用是不利于顾客的。

He has, for instance, criticised the use of loyalty card data to game the customer by offering them vouchers to switch brands.

例如，他对利用积分卡数据算计顾客、通过提供代金券诱使他们转换品牌的做法提出了批评。

It is too soon to declare the triumph of what one ex-colleague used to call big anecdote over the ideology of easy-to-measurism that has held boardrooms in thrall for the past few years.

现在要宣称我的一名前同事所称的重磅轶事相对于易于衡量观念——过去几年企业董事会牢牢奉行这种观念——取得了胜利，还为时尚早。

For example, the hastily declared failure of pollsters to predict a Donald Trump victory in the US election is more likely to be due to unsound one-on-one surveys than yawning deficiencies in wider data-gathering.

例如，有人仓促宣布民意调查机构未能预测到唐纳德.特朗普(Donald Trump)在美国大选中获胜，但预测失败的原因更有可能是不可靠的一对一调查，而不是宏观数据收集方面的巨大缺点。

The science of data analytics, when combined with cognitive computing and even neuroscientific and behavioural research, is also going to get more sophisticated and precise.

数据分析科学，跟认知计算、甚至还有神经科学与行为研究结合在一起，也将变得更先进、更精确。

For now, some of the tools measuring customer satisfaction are as blunt as those smiley-face pads you find at airports, asking you to assess your experience.

目前，有些衡量顾客满意度的工具就像你在机场发现的邀请你给旅途体验打分的笑脸打分板一样生硬。

I still wonder how the airline I flew with last summer interpreted the input from the cheerful toddler who was repeatedly stabbing the angry-face icon on the machine at our departure gate.

我仍在好奇，今年夏季我乘坐飞机的那家航空公司，对于那个开心的学步小童反复去戳登机口旁那台机器上的愤怒脸图标意味着什么如何解释。

Separately, Facebook — whose access to vast user-created troves of information retailers and airlines can only dream about — has got into trouble with its advertising customers after admitting mistakes measuring the time users spend viewing video advertisements and articles.

另外，Facebook在 广告 客户那里遇到了麻烦，因为Facebook承认，在衡量用户观看视频广告和阅读 文章 的时间上出了错误。Facebook掌握着零售商和航空公司只能梦想一番的海量用户生成信息。

Too often, computer-generated facts come close to overruling common sense.

有太多时候，计算机生成的事实几乎碾压常识。

When Pope John Paul II died in 2005, a senior editor noted that the news had surged to the top of the FT website’s most-read stories and ordered me (I was then editing our opinion pages), to commission insights into Vatican policies, Catholic mores and papal history — none of which was a hit.

当2005年教皇约翰.保罗二世(Pope John Paul II)去世时，一名资深编辑注意到，该消息已猛升至英国《金融时报》网站热门文章首位，然后命令我(当时我是观点版面的编辑)约一些有关梵蒂冈政策、天主教习俗和教皇历史的分析文章，结果这些文章没有一篇受到追捧。

Three days later, Saul Bellow died.

三天后，索尔.贝娄(Saul Bellow)去世，

His obituary also topped the rankings.

他的讣告也登上了榜首，

There was no corresponding call to deepen our coverage of US novelists and their work.

但没人打电话让我们做美国小说家及其作品的深度报道。

Insights from only a few users can still be valuable.

就算只是少数用户的意见，也可能很有价值。

Mr King advises against ignoring the shopper who complains she waited 15 minutes at the self-service tills, even if your spreadsheet shows the average wait was two minutes.

金建议，不要忽视抱怨自己在自助收银机那里等待了15分钟的顾客，即使你的电子表格显示平均等待时间是2分钟。

Her perception that it took much longer may tell you more than whole dashboards of data.

她感到等待的时间长得多，这或许能告诉你全部数据以外的东西。

Similarly, asked what Spotify would do with the customers from hell, Joakim Sundén, senior tech leader at the music streaming service, told the Drucker Forum that their deep pain might be telling you about a problem you had not identified.

同样，当被问到Spotify如何应对来自地狱的顾客时，这家音乐流媒体服务公司的资深技术主管若阿基姆.松登(Joakim Sundén)在德鲁克论坛上说，他们的深度痛苦或许正在告诉你一个你之前未曾发现的问题。

Remember, too, that there are some situations in which data may never be much help.

也要记住，在某些情况下，数据或许永远帮不上大忙。

One is innovation, where the tyranny of the business plan cramps ideas and narrows options, according to experts gathered in Vienna last week.

德鲁克论坛上的专家认为，一个是创新，专横的商业计划束缚了思想，局限了选项。

As Rita Gunther McGrath of Columbia Business School puts it: It’s always easier to go back to the spreadsheet.

正如哥伦比亚商学院(Columbia Business School)的丽塔.冈瑟.麦格拉思(Rita Gunther McGrath)所说：回去看电子表格，总是更容易的。

Roger Martin, who heads the Rotman management school’s Martin Prosperity Institute, says he would ban the word proven from organisations that wish to innovate.

罗特曼管理学院(Rotman School of Management)马丁繁荣研究所(Martin Prosperity Institute)所长罗杰.马丁(Roger Martin)说，他会禁止希望创新的机构使用经过验证的这个词。

It’s hard to explore possibilities if you have to know the answer before you start, adds Tim Brown, chief executive of Ideo.

如果你必须在开始前知道答案，那就很难探索可能性了，Ideo首席执行官蒂姆.布朗(Tim Brown)补充说。

Knowing your customer will never be a zero-sum contest between a researcher with a clipboard and IBM’s Watson.

理解你的客户，永远不是拿着带夹子的写字板的研究人员和IBM的沃森(Watson)之间的零和竞争。

Nor should it be.

也不应该是。

The best insights come from some hard-to-define blend of what you know from listening to individual users, what you can learn from their collective past behaviour and what you intuit they will want in future.

最好的理解产生于一种难以定义的混合认知：你倾听单个用户所了解到的东西，你从他们的集体过往行为中学到的东西，以及你从直觉知道他们未来想要的东西。

The really flawed assumption is that a capsule of data inserted into the analytics machine will always generate the perfect brew.

真正错误的假设是，把一些数据输入分析机器，总会生成最佳答案。

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