内容简介

“Big data” 是眼下的一个热门术语，但你知道它到底指的是什么吗？Neil 认为自己很懂 “big data”，并且可以借 “big data” 帮自己创办一家公司。菲菲对 “big data” 有自己的想法。加入我们来学习一个非常 “big” 的短语吧！

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（关于台词的备注: 请注意这不是广播节目的逐字稿件。本文稿可能没有体现录制、编辑过程中对节目做出的改变。）

Feifei
Neil, what are you doing? That’s the biggest spreadsheet I’ve ever seen!

Neil
Hi, Feifei. Yeah, just you wait. I’m developing a product that will revolutionise English teaching!

Feifei
Great! So why are you looking at screens of numbers?

Neil
Not numbers, data. Big data! This is what I need, and that's our expression in Authentic Real English.

Feifei
那你打算怎么使用这些数据呢？

Neil
I haven’t figured it out yet. But that’s not important. Everyone’s talking about big data.

Feifei
“Big data” 大数据确实是一个热门话题。但是大数据是靠分析的，你得知道如何处理这些数据。

Neil
Right.

Feifei
What you’re looking at is a list of… football scores… from every country… in 1987?!

Neil
Ah, yes. Not useful?

Feifei
Sadly not! 咱们来听听 “big data” 大数据到底是什么。

Examples
We are surrounded by data. Every time we use social media, buy something online, or even search for information, we are creating data. Because there’s so much of it, and because it comes in many forms, we call it big data.

Companies collect and analyse big data to discover hidden trends and patterns.

For example, online retailers use big data to learn what kinds of things customers like, so they can suggest new products to buy.

Feifei
这里是 BBC英语教学的 “地道英语” 节目。这集节目中介绍的表达是 “big data”。So, Neil. How’s your research going now?

Neil
Umm… not well. It’s hard to know where to start.

Feifei
我觉得你可能需要一些信息，比如用户在语言学习应用程序上的付费模式，用户登录高峰时间，登陆后在线持续的时间，不同语言水平的用户需求如何变化，第一语言的数据，哪种……

Neil
Stop, stop, stop. I’m trying to write all this down. Feifei?

Feifei
Yes?

Neil
Can I hire you as a big data analyst?

Feifei
Sorry, Neil, you’re too late. I’m launching a product of my own. It helps predict football scores. In fact, I need a bit more data from… 1987!

Neil
Ah! Well, I might just be able to help you out there!

Feifei
Yes, I think you were actually looking at my screen earlier.

Neil
Oh, sorry! You know, I think I’ll leave this big data stuff to the experts.

Both
Bye.