Unit 5 A World Full of Data 第2课时 Reading & Writing 课件 ---【中职专用】高二英语同步精品课堂（外研版2021•职业模块•工科类）

外研版 职业模块 ▪ 工科类 /Unit 5 : A World Full of Data / 第2课时 Reading & Writing Learning objectives knowledge objectives ability objectives emotional objectives draw a mind map; talk about the use of big data; describe different charts. Task 1 Read the words and expressions. Guess what the text is about. big data 大数据 volume 总量 deal with 处理 matter 要紧 source 来源 product mix 产品组合 place importance on 重视 output 产量 Task 2 Read the text and answer the questions. 1. Why is big data important? 2. What is big data used for? Task 2 Read the text and answer the questions. Big Data Big data influences almost every industry. But it is not the volume of data that is so important; it is how to deal with data that matters. Generally speaking, you can take data from many sources and analyse it to get an idea about how to reduce costs, save time, develop new products, upgrade the product mix, make smarter decisions etc. For different industries, big data can be used in different ways. In fact, big data is changing the way the world uses business information. John is the boss of a manufacturing company. He places importance on the analysis of big data, and applies the results of such analysis to his business. Compared with last year, his company has doubled output at the same cost. He believes that big data analysis has contributed a great deal because it has helped him better understand customer needs, improve product quality and make sound production plans. Task 2 Read the text and answer the questions. 1. Why is big data important? Because it influences almost every industry. Task 2 Read the text and answer the questions. 2. What is big data used for? Through the analysis of big data, people can get an idea about how to reduce costs, save time, develop new products, upgrade the product mix, make smarter decisions etc. 原文翻译 大数据 大数据几乎影响着所有行业。但是重要的并不是数据总量，而是处理数据的方式。 一般来说，你可以从许多渠道获取数据，通过数据分析，搞清楚如何降低成本、节省时间、研发新产品、升级产品组合、做出更明智的决策等。 对于不同的行业，大数据可以有不同的用途。事实上，大数据正在