Big Data Analytics: Applications, Prospects and Challenges

Vassakis, Konstantinos; Petrakis, Emmanuel; Kopanakis, Ioannis

doi:10.1007/978-3-319-67925-9_1

Cited by 193 publications

(119 citation statements)

References 13 publications

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“…However, as time passed, with confidence building measures by Cloud owners, the technology became so prevalent that most of the world's SMEs started using it in one or the other form. More information on Cloud Computing can be found in [11,12].…”

Section: Cloudsmentioning

confidence: 99%

Information technologies of 21st century and their impact on the society

Yamin

2019

Int. j. inf. tecnol.

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Twenty first century has witnessed emergence of some ground breaking information technologies that have revolutionised our way of life. The revolution began late in 20th century with the arrival of internet in 1995, which has given rise to methods, tools and gadgets having astonishing applications in all academic disciplines and business sectors. In this article we shall provide a design of a 'spider robot' which may be used for efficient cleaning of deadly viruses. In addition, we shall examine some of the emerging technologies which are causing remarkable breakthroughs and improvements which were inconceivable earlier. In particular we shall look at the technologies and tools associated with the Internet of Things (IoT), Blockchain, Artificial Intelligence, Sensor Networks and Social Media. We shall analyse capabilities and business value of these technologies and tools. As we recognise, most technologies, after completing their commercial journey, are utilised by the business world in physical as well as in the virtual marketing environments. We shall also look at the social impact of some of these technologies and tools.

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Section: Cloudsmentioning

confidence: 99%

Information technologies of 21st century and their impact on the society

Yamin

2019

Int. j. inf. tecnol.

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“…Descriptive analytics also is known as diagnostic analytics which is used to analyze and answer on what happened in past and present and why it is happening whether it was success or failure in easily understandable form by using visualization tools and online analytical processing (OLAP) system to support real-time information [28,35]. These analytics has advantages including to view the data in the real world context, identify relevant information from the data, produces the quality of data and recognize the assumptions or limitation of the findings.…”

Section: A Descriptive Analyticsmentioning

confidence: 99%

“…The basis for this analytics is based on probability. There are various techniques such statistical models, machine learning, data mining and data modeling can be implemented by organizations to discover the pattern and its relations in data for forecasting and as a weapon for a business competitive race [35,36].…”

Section: A Descriptive Analyticsmentioning

confidence: 99%

“…Prescriptive analytics is used for forecasting but focuses on impact in future actions before responding to the outcome about what might happen with the organization's action based on consideration of descriptive and predictive analytics to make it more efficient [28,35]. It one of the most complex and advanced forms of analytics compare to another.…”

Section: Prescriptive Analyticsmentioning

confidence: 99%

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A Review on Student Attrition in Higher Education Using Big Data Analytics and Data Mining Techniques

Tarmizi¹,

Mutalib²,

Hamid³

et al. 2019

IJMECS

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Student attrition among undergraduate students is among the most concerned issues in higher educational institutions in Malaysia and abroad. This problem arises when these students unable to complete their studies within the stipulated period when there are majoring in the Science, Technology, Engineering, and Mathematics (STEM) fields. Research findings highlight numerous factors contribute to the student attrition. These findings also suggest that the factors differ from one case to another case. Effects of student attrition not only for the student itself but also to the institutions and community. It is challenging to classify the factors based on general assumptions. Moreover, increasing students' information makes the problem more complicated. This student information can provide a useful database for analytical analysis. Methods such as big data analytics and data mining techniques can be deployed to gain insights and pattern that related to student attrition problem. The objective of this paper (i) review the student attrition in higher education (HE) and the contributing factors; and (ii) review the existing computational model to analyze and predict student attrition in HE.

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“…We recognize that data processing is the most important phase of the whole process as the success of the analysis strongly depends on it and may consume up to 90% of the time and resources [37]. Descriptive and diagnostic analytics [25,34] are key tools for acquiring insight of any dataset. In addition, it is recognized that in data science, especially 'big data' research, the full documentation of the methods and the replicability of the results is a critical issue and often remains unaddressed in research [3,4].…”

Section: Introductionmentioning

confidence: 99%

Visualising maritime vessel open data for better situational awareness in ice conditions

Jussila

Lehtonen²,

Laitinen³

et al. 2018

Proceedings of the 22nd International Academic Mindtrek Conference

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Situational awareness of maritime vessels in ice conditions is important for the operation of supply chains. In the artic sea areas, the ice conditions pose a major challenge for maritime vessels getting stuck in the ice and being significantly delayed in arrival to harbor. Data science and open data provide new opportunities to overcome these challenges. This paper introduces available open data sources and data visualizations that can be used to develop applications, for example, for detecting maritime vessel collision, predicting estimated time of arrival to harbor, as well as maritime vessel route optimization in ice conditions. The paper begins by introducing available open data sources and existing computational studies on maritime vessels in ice conditions, then presents the developed data science solution and visualizations of the open data along with the open source software code, and finally concludes with a discussion on the potential application areas and opportunities for further research.

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Big Data Analytics: Applications, Prospects and Challenges

Cited by 193 publications

References 13 publications

Information technologies of 21st century and their impact on the society

Information technologies of 21st century and their impact on the society

A Review on Student Attrition in Higher Education Using Big Data Analytics and Data Mining Techniques

Visualising maritime vessel open data for better situational awareness in ice conditions

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