Если у вас возникли сложности с курсовой, контрольной, дипломной, рефератом, отчетом по практике, научно-исследовательской и любой другой работой - мы готовы помочь.
Предоплата всего
Подписываем
Образец выполнения зачетной работы по дисциплине
«Реферирование и аннотирование»
Задание 1. Выполните предварительный анализ текста, составьте план текста и реферат статьи:
Welcome to the yotta world
Even if you still have to think twice about the meaning of “giga” and “tera” in computer-speak, you’d better get ready for “peta”, “exa” and “zetta”. These binary prefixes, which denote 1m, 1 billion and 1 trillion gigabytes respectively, will be used more and more often: the amount of digital data is exploding, with a staggering 1.8 zettabytes in 2011, up from 1.2 zettabytes in the previous year. This deluge has long been a topic among geeks; 2012 will be the year in which the Big Data trend gets noticed beyond their ranks. Many more firms will start to analyse huge piles of data to optimize everything from their supply chains to their customer relationships.
In the past, because data storage was expensive, lots had to be thrown away. Information was locked up in computer systems and could not be combined with other sources. Even if firms were able to aggregate their data in one place (called a “data warehouse”) and sift through the information, it was often already out of date.
All this is changing — rapidly. The price for storage is plunging; by 2020 storing a petabyte will cost a mere $4, predicts Forrester, a market-research firm. Software to handle such huge amounts of data is improving, too. Hadoop, a new type of database, can be used to sift through big data streams in real time — and not just orderly numbers, but also “unstructured” data, for instance any kind of text.
In a world oozing data, sensors measure everything from speed to smell. Smartphone applications generate vast quantities of “data exhaust”: information that is produced when users engage in, say, skiing, and, thanks to a motion sensor, the phone can tell whether somebody has just had a bad fall. Social media are adding to the flood: the number of messages on Twitter will exceed 500m per day by the end of 2012. By opening their data vaults, some national and local governments are doing the same.
Most important, firms will discover that they can extract value from the data. A study by the McKinsey Global Institute, a think-tank, found that analysing health-care data could yield $300 billion-worth of savings in America alone. One of the pioneers in this field is Britain’s National Institute for Health and Clinical Excellence, which uses large datasets to investigate the cost and benefit of new drugs and existing expensive treatments.
Firms will also use data for new business models. Rolls-Royce no longer needs to sell all its jet engines; it can charge for their use. By continuously assessing their performance, it can predict when engines are more likely to fail, so that customers can schedule engine changes. Already, the number of data-driven start-ups is growing — particularly when it comes to social media. Lexalytics, for instance, analyses the sentiment of utterings on Twitter, Facebook and other such services. Klout measures the influence of social-media users (and some firms give people with a high Klout score preferential treatment).
For Big Data to become huge, however, there are still hurdles to leap. For one thing, the tools to analyse data are not yet good enough. And people with the skills to analyse data are scarce and will become scarcer. By 2018 there will be a “talent gap” of between 140,000 and 190,000 people, says the Mc Kinsey Global Institute. The main problem may be privacy. It is unlikely that people will want to live in a “yotta world” (1,000 trillion gigabytes) in which their every move is instantly digitised and added to the flood of public data.
Абзац 1:
З топик
Т объяснение (почему you’d better get ready for “peta”, “exa” and “zetta”)
К Ø
Абзац 2:
З ссылка на основе противопоставления (in the past vs in the future в первом абзаце)
Т описание (ситуации с data storage в прошлом)
К Ø
Абзац 3:
З топик., ссылка на основе сравнения (т.к. this, i.e. the past situation is changing)
Т описание (каковы эти rapid changes)
К Ø
Абзац 4:
З ссылка
Т описание (какова ситуация (the world of oozing data) сейчас)
К Ø
Абзац 5:
З топик, ссылка на предыдущий текст
Т рассуждение (доказывает, что фирмы действительно смогут extract value from the data)
К Ø
Абзац 6:
З топик, ссылка
Т рассуждение (доказывает, что фирмы действительно смогут use data for new business models)
К Ø
Абзац 7:
З топик, ссылка на основе противопоставления (however) на предыдущие радужные перспективы
Т рассуждение (доказывает, что действительно for Big Data to become huge there are still hurdles to leap)
К Ø
План:
1 (абзац 2) Ситуация в прошлом
2 (абзац 3,4) Ситуация в настоящем
3 (абзац 1, 5-7) Прогноз
Реферат:
1. In the past information:
- was expensive to store;
- had to be often thrown away;
- was locked up in computer systems;
- could not be combined with other sources;
- became out of date fast.
2. All this is rapidly changing into a world of oozing data thanks to:
- plunging price for storage;
- improving software for handling huge amounts of data.
3. In the future firms will discover that:
- they can extract value from the data;
- use data for new business models.
There are still hurdles to leap as:
- tools to analyse data are not yet good enough;
- people with the skills to analyse data are scarce;
- the problem of privacy may persist.