• Journal of Digital Convergence
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• v.13 no.10
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• pp.51-58
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• 2015

The utilization of Big data in the field of education has spread around the developed countries. However, in Korea, there are only experimental approaches related to Bigdata, yet for the related researches and services to appear. Therefore, it is the situation that needs to understand the reason for poor use of big data in the e-Learning industry, study and seek out alternatives to solve these problems. The result of this study shows that it was investigated that the high level of understanding of Bigdata has recognized large impact on e-Learning of Big Data and the more large-scale sales companies have recognized large impact on e-Learning of Big Data in the e-Learning industry. In conclusion, this study makes a proposal to expand the training and utilization policies of Bigdata relating to different sales scales.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.241-248
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• 2014

It has been expanded the bandwidth of data usages due to the rapid developments of information technology and infra hardware and then it was proposed to new paradigm of Big Data era. It has a trend to increase a Big Data technology and its performance gradually, thus enterprises have realized the importance of Data and the movement to take advantage of Big Data becomes active. This study has been performed to verify the importance through select the factors in order to active adoption of Big Data technology and utilization when enterprises use Big Data. It was selected that Big Data characteristic factors are the natures of predictability, manageability, affordability, competitiveness, creativity, responsiveness and supportability on the study. It is verified and showed that manageability were influenced to introduce Big Data in order, at the result of survey and statistics for enterprise practitioners who have big data experience.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.341-347
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• 2014

Among methods of the big data process, big data process under the cloud environment is becoming a main topic. As part of solving faced problem and strengthening industrial competitiveness in the medical and health industry, discussion on ways to activate big data is actively being conducted. Because the reason is a paradigm shift, saving pressure for increasing health care costs, and increased consumer interest for the level of service. In this paper, we find out the relationship between the cloud and big data. And we are to research and analysis a cloud-based big data case in the medical field. Finally we propose the efficient utilization and future outlook. For the smooth functioning of cloud-based medical big data, we have to solve the problems like infrastructure extension, analysis/application software development, and professional manpower training. In addition, we have to correct insufficient laws maintenance to the Cloud utilization, and improve the security and the recognition to personal information, and solve authority for data centralization.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.61-69
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• 2017

This study aims to investigate the public big data standard analysis model developed by Ministry of the Interior and examine its accuracy and reliability of prediction. To do this, big data standard analysis index were calculated to apply them to the real world case of CCTV monitoring system prior installation in K city. The result of this case study revealed that the areas to be installed CCTV consisted with the area where residences requested and complained to install CCTV monitoring systems, which indicated that the result of big data standard analysis model provided accurate and reliable outcomes. The result of this study suggested implications on effective exploitation of big data analysis.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.167-178
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• 2017

Big Data is a key asset for the company and a key factor in boosting its competitiveness in the logistics sector. However, there is still a lack of research on how to collect, analyze and utilize Big Data in logistics. In this context, this study has developed a value model applicable to logistics companies based on the results of analysis and application of Big Data in the logistics of previous studies and DHL. The purpose of this study is to improve the operational efficiency and customer experience maximization level of logistics companies through utilization of big data analysis in logistics, to improve competitiveness of big data utilization and to develop new business opportunities. This study has a significance to newly create a value model for utilization of big data analysis in logistics sector and can provide implications for other industries as well as logistics sector in the future.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.185-194
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• 2015

We are living in big data. Specially, female consumers are the hottest issue. Female consumers have a great effected on consumer culture as comparing male consumers. Therefore, this study analysis characteristics of female consumers through case study and literature review. The summarized results of research are as follows. First, percentage of economically active population of unmarried female of 20s is high, so they actively spend lots of money on buying goods and so on. Second, they are ahead of the curve and follow entertainers. Third, domestic case studies(SD online buz marketing, C.S.I. Shinsegaemall project, Service center only for female consumers of Shinhan Card, Travel Service of Lotte Tour) and international case studies(Big data service of Target, ZARA, and Walmart) show that if we utilize big data, we can raise re-purchasing desire and analysis needs of female consumers and create new female consumers.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.237-253
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• 2018

In a rapidly changing environment, dynamic resources have become important factors for companies, the use of Big Data come into focus new core value of business but researches on the major resources and capabilities of companies are insufficient. In this study, the effect of dynamic capability and entrepreneurial orientation in the SMEs on the intention of Big Data utilization are explored. For the purpose of empirical analysis, the survey condusted of 364 domestic SMEs to analyze the effect of dynamic capability on the intention of Big Data utilization through entrepreneurial orientation, performed a parallel multi-parameter analysis of using SPSS Win Ver.22.0 and PROCESS macro v3.0. The results of hypothesis testing showing that dynamic resources and entrepreneurial orientation had positive influence intention of big data utilization. For the determinants of Big Data utilization related to AI it provide suggestions thereby improving the understanding of dynamic capabilities and entrepreneurial orientation and helping to improve the management of SMEs.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.305-315
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• 2020

As the incidence and prevalence of dementia increases with our aging population, so does the social burden on our society, which calls for a special emphasis on need for early diagnosis. Thus, efforts are made to prevent dementia and early detection but with current diagnostic measures, these efforts appear futile. As a solution, it is crucial to integrate and standardize healthcare big data and analysis of each index. In order to increase use of large database, the Korea National Assembly passed the Data 3 Act focusing on open-access and sharing of database, but a follow-up legislation is needed a for safer utilization. In this study, we have identified number of foreign of foreign policies through review of prior researches on the topic leading to specific enforcement ordinances tailored to the Data 3 Act for safe access and utilization of database. We also aimed to establish secure process of data collection and disposal as well as governance at the national level to ensure safe utilization of healthcare big data.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.21-27
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• 2016

Big Data is gathering all the attention from every business community. Pervasive use of machine-to-machine (M2M) applications and mobile devices bring an explosion of data. By analyzing this data, the private and public sectors can benefit in the areas of cost reduction and productivity. The Korean government is actively pursuing Big Data initiatives to promote its usage. This paper aims to select industries which fit for the development of Big Data with a verification of the experts. The analytic hierarchy process (AHP) is applied to systematically derive the opinion of more than 50 professionals. Medical / welfare, transportation / warehousing, information and communications / information security, energy, the financial sector have been identified as promising industries. The results can be utilized in developing Big Data best practices thus contributing industrial development.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.105-115
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• 2021

Many services are provided through big data analysis in various fields such as individuals, private sectors, and governments. There is a growing interest in training data scientists to provide these services. Particularly, interest in big data-based marketing curriculum is high. This study analyzed the domestic and foreign university big data-based marketing-related curriculum to utilize vast and diverse types of information from a marketing perspective in the era of big data. As a result of the analysis of 3,523 subjects related to digital marketing, big data marketing, data analysis, and developers collected according to the analysis criteria, it was analyzed that the specialized curriculum for training data scientists required in the era of the fourth industrial revolution was not appropriate. It is expected that the proposed curriculum in this study will be useful for the development of digital marketing and big data-based marketing curriculum.