• The Journal of Information Systems
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• v.30 no.1
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• pp.21-44
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• 2021

Purpose The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field. Design/methodology/approach This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data. Findings We identified seven sub- areas of business analytics field. The top four sub-areas are "Big Data Analytics Infrastructure", "Performance Management System", "Interactive Exploration", and "Supply Chain Management". We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

• Asia Marketing Journal
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• v.14 no.3
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• pp.1-5
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• 2012

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.114-116
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• 2016

Today, the analysis of big data hae been used as an essential tool for finding customers' needs. Various big-data analysis sites have provided the analysis results with their own forms and styles according to their service and characteristics. Therefore, to use the analysis results for marketing fields, we have to understand the major characteristics on big data analysis tools. In this point, this study attempts to compare the characteristics of big data analysis results and styles from big data analysis sites.

• Convergence Security Journal
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• v.21 no.1
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• pp.73-78
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• 2021

Big data is a key driver of the fourth industrial revolution, represented by ultra-connected, ultra-intelligence, and ultra-convergence, and it is important to create innovation and share, link, and utilize data to discover business models. However, it is difficult to secure and utilize high-quality and abundant data when big data platforms are built in a regular manner without considering shared-linked. Therefore, this paper presents the development direction of big data platform infrastructure by comparing and analyzing various cases of big data platforms to enable data production, construction, linkage, and distribution.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.290-296
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• 2022

Big Data is a data analysis technology empowered by late advances in innovations and engineering. In any case, big data involves a colossal responsibility of equipment and handling assets, making reception expenses of big data innovation restrictive to little and medium estimated organizations. Cloud computing offers the guarantee of big data execution to little and medium measured organizations. Big Data preparing is performed through a programming worldview known as MapReduce. Normally, execution of the MapReduce worldview requires organized joined stockpiling and equal preparing. The computing needs of MapReduce writing computer programs are frequently past what little and medium measured business can submit. Cloud computing is on-request network admittance to computing assets, given by an external element. Normal arrangement models for cloud computing incorporate platform as a service (PaaS), software as a service (SaaS), framework as a service (IaaS), and equipment as a service (HaaS).

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.6
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• pp.185-194
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• 2016

Recently, as the popularization of the mobile and the internet, the need of big data technology using a vast amount of data which contains the information has emerged. Big data technology has been used in various fields but use of the public sector is still insufficient. So, this study applies them. This study explores factors influencing silver industry as keywords, graving has effect on the present as well as future society. Results, five variables are 'silver Industry', 'senior citizen who lives alone', 'aging', 'birth' and 'retirement' were searched, and it was confirmed that they are correlated with one another. Results of analyzing the influence of the other four parameters on "Silver Industry", they have an effect significantly. In addition, it proposed the need of the 'providing living space of senior citizen who lives alone', 'childbirth support policy', 'support to vitalize silver startup senior manpower of technology' as an alternative to develop the silver industry. This study provided the theoretical implications that is exploring factors through a quantitative approach using big data and the practical implication is to suggest an alternative.

• The Journal of Bigdata
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• v.1 no.1
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• pp.77-84
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• 2016

We investigate the types and characteristics of Fintech has become a major issue. Through this, we believe that the essence of Fintech are platform business and market occupancy. To success Fintech business, the price of Fintech services needs to be lower than that of traditional financial services. The solution is to take advantage of big data and big data analysis. Finally, we think only a win-win cooperation with Fintech startups and financial companies in the direction we need to go.

• Advances in nano research
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• v.14 no.1
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• pp.67-80
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• 2023

Economic investigation is one of the main issues regarding the design and production of small-scale structures. This paper concerns the creation, implementation, and economic aspects of the cross-section profile of small-scale structures regarding the dynamic response of the free and forced vibration behavior of spinning nanoscale beams based on big data analysis. According to the financial analysis, the three practical non-uniform functions of cross-sections are compared to the uniform beam in the same weight and the equal material used. The previous studies reported that the uniform beams are more stable and contain a better frequency response based on the mechanical analysis. Still, concerning the economic investigation, which means the considered structures should have equal length and have the same weight in the aspect of material used, the conclusion can be different from the mechanical aspect. Consequently, in the current paper, the dynamic response along with computer technology as well as the big data analysis of the free and forced vibration of the nanobeam regarding the economic shape of the cross-section is scrutinized.

• Journal of Practical Engineering Education
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• v.12 no.1
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• pp.31-39
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• 2020

Big data analysis is analyzed and used in a variety of management and industrial sites, and plays an important role in management decision making. The job competency of big data analysis personnel engaged in management analysis work does not necessarily require the acquisition of microscopic IT skills, but requires a variety of experiences and humanities knowledge and analytical skills as a Data Scientist. However, big data education by state-run and state-run educational institutions and job education institutions based on the National Competency Standards (NCS) is proceeding in terms of software engineering, and this teaching methodology can have difficult and inefficient consequences for non-technical majors. Therefore, we analyzed the current Big Data platform and its related technologies and defined which of them are the requisite job competency requirements for field personnel. Based on this, the education courses for big data analysis and visualization techniques were organized for non-technical-based majors. This specialized curriculum was conducted by working-level officials of financial institutions engaged in management analysis at the management site and was able to achieve better educational effects The education methods presented in this study will effectively carry out big data tasks across industries and encourage visualization of big data analysis for non-technical professionals.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.681-689
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• 2019

The 46th Davos Forum of the World Economic Forum (WEF) predicts the continued growth of the 4th industry in the future. Currently, the 4th industry is attracting attention in various academic and practical fields. As a core technology of the 4th industry, Big Data is regarded as a major resource to lead the 4th industrial revolution along with artificial intelligence. As the growing interest in Big Data, researches on it are actively being done. However, literature studies on existing Big Data are focused on qualitative research, and quantitative research is insufficient. Therefore, this study aims to analyze the big data research flow in MIS field and to make academic thirst for quantification. This study has collected 145 abstracts of big data papers published in major journals in MIS field and confirmed that a majority of papers are published in Decision Support Systems Journal. Text mining and text network analysis were performed only for DSS journals to eliminate bias. As a result of the analysis, it was found out that researches on combining big data in the management field between 2012 and 2014, and researches on system development and analysis method for using big data from 2015 to 2017 were conducted.