data explosion
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2022 ◽  
pp. 1734-1744
Author(s):  
Jayashree K. ◽  
Abirami R.

Developments in information technology and its prevalent growth in several areas of business, engineering, medical, and scientific studies are resulting in information as well as data explosion. Knowledge discovery and decision making from such rapidly growing voluminous data are a challenging task in terms of data organization and processing, which is an emerging trend known as big data computing. Big data has gained much attention from the academia and the IT industry. A new paradigm that combines large-scale compute, new data-intensive techniques, and mathematical models to build data analytics. Thus, this chapter discusses the background of big data. It also discusses the various application of big data in detail. The various related work and the future direction would be addressed in this chapter.


Author(s):  
Ruaa Alsabah ◽  
Mustafa Aljshamee ◽  
Ammar M. Abduljabbar ◽  
Ali Al-Sabbagh

The internet is considered to be the most advanced technology today and a gateway to modern communication and the sharing of information, products, services, and technology. Nowadays, users want to be able to access anywhere and anytime several services and applications, which is increasing data traffic and triggering a mobile data explosion. Iraq has major problems in increasing the growth and use of the internet and changing the standard method of communication. This is a big challenge, however, since there are several variables that characterize this phase of transformation. In this paper, the problems, vision, and solutions are presented in details. This study aims to clarify the factors of internet use in Iraq by the use of an acceptable approach and by suggesting new solutions for all the presented problems. This work also, clarify the expected traffic and the mechanism to transform the traffic between local ISP’s networks (AS) internet exchange points.


2021 ◽  
Vol 14 (4) ◽  
pp. 57
Author(s):  
Paras Gulati ◽  
Abiodun Adeyinka. O. ◽  
Saritha Ramkumar

The rapid spread of online fake news through some media platforms has increased over the last decade. Misinformation and disinformation of any kind is extensively propagated through social media platforms, some of the popular ones are Facebook and Twitter. With the present global pandemic ravaging the world and killing hundreds of thousands, getting fake news from these social media platforms can exacerbate the situation. Unfortunately, there has been a lot of misinformation and disinformation on COVID-19 virus implications of which has been disastrous for various people, countries, and economies. The right information is crucial in the fight against this pandemic and, in this age of data explosion, where TBs of data is generated every minute, near real time identification and tagging of misinformation is quintessential to minimize its consequences. In this paper, the authors use Natural Language Processing (NLP) based two-step approach to classify a tweet to be a potentially misinforming one or not. Firstly, COVID -19 tagged tweets were filtered based on the presence of keywords formulated from the list of common misinformation spread around the virus. Secondly, a deep neural network (RNN) trained on openly available real and fake news dataset was used to predict if the keyword filtered tweets were factual or misinformed.


Author(s):  
Tejinder P. Singh ◽  
Jessica Zaman ◽  
Jessica Cutler

2021 ◽  
Author(s):  
Md. Abdul Malek

<p></p><p><i>With the data landscape of the universe expands every second every day by leaps and bound, the data value also increases unprecedentedly. Particularly, the disruptive use of data in location tracking, predictive policing, fraud detection, healthcare, advertising media, and entertainment has already revitalized personal data in many ways. But massive amassing of data also gives rise to new issues regarding the Big Data effects, including privacy invasion, data breaches, and cyber threats, etc. Taking effective efforts for mitigating the risks of data explosion thus becomes indispensable for companies, organizations, and societies alike. In such background, this paper attempts to focus on the ways how the data minimization approach mitigates such risks, and how this approach as a concept is being incorporated in legal instruments globally. After exploring practical methods of applying data minimization, the paper concludes by delineating the way out of the existing dilemmas so created in the face of Big Data. </i></p><br><p></p>


2021 ◽  
Author(s):  
Md. Abdul Malek

<p><i>Over 4.1 billion internet users of the universe generate about 2.5 quintillion bytes of data each day; and a digital universe of 44 zettabytes will hit 2021. As the data landscape expands every second every day, the data value also increases by leaps and bound. Personal data then get revitalized for the disruptive use of location tracking, predictive policing, fraud detection, healthcare, advertising media, and entertainment. Likewise, massive amassing of data also at the same pace gives rise to some new issues regarding the Big Data effects, including privacy invasion, data breaches, and cyber threats, etc. Taking efforts for mitigating the risks of data explosion thus becomes imperative for the society we live in. Accordingly, this paper attempts to focus on the ways how the data minimization approach mitigates such risks, and how this approach as a concept is being incorporated in the legal instruments. After suggesting practical methods on how to reap benefits from the principle, the paper concludes by exploring the way out of the existing dilemmas so created in the digital transformation. </i></p>


2021 ◽  
Author(s):  
Md. Abdul Malek

<p><i>Over 4.1 billion internet users of the universe generate about 2.5 quintillion bytes of data each day; and a digital universe of 44 zettabytes will hit 2021. As the data landscape expands every second every day, the data value also increases by leaps and bound. Personal data then get revitalized for the disruptive use of location tracking, predictive policing, fraud detection, healthcare, advertising media, and entertainment. Likewise, massive amassing of data also at the same pace gives rise to some new issues regarding the Big Data effects, including privacy invasion, data breaches, and cyber threats, etc. Taking efforts for mitigating the risks of data explosion thus becomes imperative for the society we live in. Accordingly, this paper attempts to focus on the ways how the data minimization approach mitigates such risks, and how this approach as a concept is being incorporated in the legal instruments. After suggesting practical methods on how to reap benefits from the principle, the paper concludes by exploring the way out of the existing dilemmas so created in the digital transformation. </i></p>


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