Big Data: Survey, Technologies, Opportunities, and Challenges

Abstract

Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.

The role of big data in smart city

“…Consequently, such enormous volumes of data or big data are at the core of the services rendered by the IoT. The phenomenon of big data has long been characterized by volume, velocity, and a variety of data types that have been created at everincreasing rates (Khan et al, 2014). Big data offers the potential for the city to obtain valuable insights from a considerable amount of data collected through various sources.…”

Didžiųjų Duomenų Naudojimas Klientui Pažinti / Model of the Big Data Use for Customer Cognition

“…Siekiant tikslesnio didžiųjų duomenų sąvokos apibrė-žimo, pasiūlytas 7V modelis (Khan et al, 2014;Seddon ir Currie, 2017). Formuojant šį modelį, pridėtos pagrįstumo (angl.…”

“…Ši charakteristika neretai tapatinama su teisingumo charakteristika, tačiau jos skiriasi. Pagrįstumu apibūdinamas duomenų logiškumas, atitiktis faktams (Khan et al, 2014). Yra tikrinama, ar duomenys turi tokią prasmę, kuri jiems priskiriama.…”

“…D. Boyd ir K. Crawford (2012) Laney, 2001;Zakir, 2015;Kaur et al, 2016;Khan et al, 2014;Seddon ir Currie, 2017) Figure 1. Models of big data (composed by the authors based on Laney, 2001;Zakir, 2015;Kaur et al, 2016;Khan et al, 2014;Seddon & Currie, 2017) mas, praktikas, metodologijas ir programas, skirtas verslo duomenų analizei, dėl kurios įmonė galėtų laiku priimti sprendimus ir geriau suprastų savo verslo modelį bei rinką (Chen, Chiang ir Storey, 2012). Kadangi verslo analitikos sritis sparčiai plečiasi ir vis daugiau įmonių renka ir analizuoja didžiuosius duomenis, su didžiaisiais duomenimis pradėtos glaudžiai sieti saugumo ir privatumo sąvokos.…”

A Study on the Influence of the use of Social media on College Students

“…In order to grasp the students' use of social media and understand its influence on College Students' daily life, social communication and so on, we focused on students in Colleges and universities in Heilongjiang province to carry out a survey of [2], brought about mainly from the use of social media, time, frequency and social media use in the process of psychological change and other aspects. Through face-to-face and online research methods were 1000 questionnaires, in order to understand the rapid development of the Internet today, intelligent mobile phone, tablet computer is highly popular in the university campus, the impact of social media on Contemporary College students.…”