Some features of Big Data and its applications in life

Posted date 08/06/2016

14.537 view

Posted date 08/06/2016

14.537 view

Nowadays, the constant development of science and technology, typically the birth of the Internet and mobile devices and personal computers, has brought about great changes in all areas of life.

Nguyen Ngoc Minh - Department of Scientific Research and International Cooperation

Nowadays, the continuous development of science and technology, typically the birth of the Internet and mobile devices, personal computers, has brought about great changes in all areas of life. In the era of IoT2, with the widespread application and integration of mobile devices such as mobile phones, cars, and industrial machines, contributing to the creation and transfer of data, leading to an explosion of collectible data. In the continuous flow of data generated every second, the term Big Data is used to refer to huge, mostly unstructured data sets collected from many different sources. However, Big Data contains a lot of valuable information that, if successfully extracted, will greatly help business, scientific research, predicting upcoming epidemics, and even determining traffic conditions in real time. In scientific research, Big Data is giving researchers the opportunity to approach and solve many difficult problems that were previously impossible or very difficult to do. Through this article, the author wants to introduce the increasingly popular concept of Big Data and its applications in today's life.

A. Definition and characteristics of Big Data
Big Data is a term used to describe data sets that are very large in size, grow rapidly, and are very difficult to collect, store, manage, and analyze with traditional statistical tools or database applications. According to an IDC report, in 2011, the amount of data created in the world was 1.8ZB3, an increase of nearly 9 times in just 5 years. The size of Big Data is increasing day by day, and as of 2012, it can range from a few dozen terabytes to many petabytes (1 petabyte = 1024 terabytes) for just one data set. According to Le & Nguyen (2014), there are 4 main characteristics used to describe Big Data including Volume, Velocity, Variety, and Value:
Volume: The volume of Big Data is growing exponentially. According to Intel's September 2013 report, every 11 seconds, 1 petabyte of data is created worldwide, equivalent to 13 years of HD video.
Velocity: The speed at which data is analyzed by companies to provide a better user experience. With the advent of new techniques, tools, and storage applications, data sources are continuously being added at a rapid pace. McKinsey Global estimates that the amount of data is growing at a rate of 40% per year, and will increase 44 times from 2009 to 2020.
Variety: Data is collected from many different sources, from sensors, mobile devices, social networks, etc.
Value: is the process of extracting the huge values hidden in huge data sets. This is the most important feature because the information extracted from Big Data analysis can be used in many fields such as business, scientific research, medicine, physics, etc.

B. Some applications of Big Data in life
Big Data is increasingly being used in many fields and organizations for many different purposes. For example, companies use Big Data to understand customer consumption behavior and then make personalized shopping recommendations for each subject based on the information collected from them (Ebay, Facebook, Google, etc.). Scientific research facilities use Big Data to find new scientific discoveries for humanity, such as building a human genome map, or typically research at the Hadron accelerator of the European Organization for Nuclear Research. If the results obtained from the sensors in the machine are fully recorded, the data flow will become extremely large, possibly reaching 150 million petabytes per year, 200 times more than all other data sources in the world combined.

With the increasing popularity of information technology, Big Data is a topic that has received a lot of attention from researchers. Hsinchu & Chiang (2012) analyzed the applications of Big Data in the fields of e-commerce, e-government, science and technology, and health care. O'Leary (2013) mentioned the application of Big Data in road infrastructure management. When the Sloan Digital Sky Sruver, a space observatory located in New Mexico, started operating in 2000, after a few weeks it collected more data than the total amount of data that astronomy had ever collected in the past, about 200GB per night and now the total capacity has reached more than 140 terabytes. In 2016, when the LSST observatory replacing SDSS comes into operation, it is expected to collect the same amount of data as above but within only 5 days (Duy Luan, 2013).
According to Le & Nguyen (2014), in the field of commerce in particular, big data analysis also contributes to improving and optimizing the decision-making process, minimizing risks, and creating added values for businesses. By exploiting the big data analysis platform, businesses can discover huge potential values, through comprehensive views of customer purchasing behavior. For example, online businesses can not only track to know not only information such as what customers buy, but also know what items they view, what they see, what they do each time they visit the website, or the extent to which customers are affected by promotional policies or comments from other customers; thereby discovering commonalities of customer groups.
It can be said that Big Data, although only recently mentioned, is still being increasingly researched and widely applied in many other fields. However, within the framework of this article, the author only summarizes some of the characteristics and applications of Big Data in the fields. In the following articles, the author will analyze more thoroughly the conflicting opinions about the benefits and limitations of Big Data.

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