• Journal of Digital Convergence
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• v.13 no.11
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• pp.25-33
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• 2015

In Korea, despite the increase in demand for Bigdata manpower, institutions and universities to educate and train Bigdata manpower are not yet much. Therefore, this study investigated the status regarding the recognition on Bigdata of universities students and presented a direction for educating Bigdata manpower at the university. In order to accomplish this purpose, this study surveyed and analyzed the students' understanding of Bigdata, the awareness of the students about the social impact of Bigdata, the learning intention of the students on Bigdata and presented Implications for Bigdata workforce development. As a result, despite of the somewhat difference in understanding for the Bigdata, it was found that their awareness about the impact of Bigdata is very positive. And this study showed the need of universities' and government' political effort for Bigdata workforce development, because it was investigated that students' intentions of learning for Bigdata is proportional to students' understanding levels and learning experience for Bigdata.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.17-25
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• 2017

Horizon scanning that one of the methods for future prediction is adaptable way of establishing the policy strategy based on big data. This study aims to understand the social problems scientifically utilized horizon scanning technique, and contribute to public policy formulation based on scanning analysis. In this paper, we proposed a public opinion framework for public policy based on social bigdata, and then confirmed the feasibility this framework by analysis of the relationship between public opinion and results after implementation of public policy. Consequently, based on the analysis, we also drew implications of policy formulation about 'free childcare for under 5-years of age' as an object of study. The method that collects public opinion is very important to effective policy establishment and make contribution to constructing national response systems for social development.

• Journal of Digital Convergence
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• v.18 no.9
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• pp.39-47
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• 2020

This study was conducted with the aim of investigating the actual state of data utilization and the perception of big data utilization by officials of the provincial Office of Education and to derive implications for the establishment of strategies for big data utilization. An online survey of 440 people was conducted. As a result, the types and sources of data used for work varied, and data collection and refining were the most difficult parts. The infrastructure for data utilization was insufficient and the most necessary factor. The purpose of big data utilization was related to the establishment of educational policy agenda.

• 한국벤처창업학회:학술대회논문집
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• 2020.11a
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• pp.47-53
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• 2020

빅데이터 기술은 기업의 경쟁력을 높일 수 있는 혁신 기술 중 하나로 급성장하고 있는 가운데 농업 분야 또한 빅데이터를 활용한 경쟁력 제고와 미래 산업으로의 발전이 중요 당면과제로 부상하고 있다. 해외의 경우 농업 빅데이터를 활용한 스타트업이 빠른 속도로 증가하며 성장하는 반면 국내의 경우 생산 분야 일부 농업 벤처 외에는 빅데이터 활용이 미흡한 실정이다. 또한 기업의 빅데이터 활용수준이나 활용의도에 영향을 미치는 요인에 대한 연구가 대기업이나 특정 산업에 국한되어 이루어지고 있으며, 연구마다 영향요인 변수의 검증결과가 상이하게 나타나 산업/기업특성에 따라 연구가 필요하다. 본 연구의 목적은 농업벤처기업에서 새로운 ICT인 빅데이터를 도입하고 사용하는 데 영향을 미치는 요인을 파악하고, 이를 통해 기대하는 편익에 대해 파악함으로써 활용을 촉진할 수 있는 방안을 제시하는 데 있다. 본 연구는 빅데이터가 조직의 프로세스를 변화시키고, 최고경영층의 지원이 필수적이며, 기업이 처한 환경적 압박에 대응할 수 있는 수단으로 보고 기술·조직·환경(TOE: Technology-Organization-Environment) 프레임워크를 기반으로 혁신확산이론(Diffusion of Innovation Theory) 모형을 결합하여 본 연구에 적합한 변수들을 도출한 후 이들 변수간의 인과관계를 설정하여 연구모형을 구성하였다. 이에 따라 TOE모형의 기술적 요인에 관한 변수로는 혁신확산이론 변수인 상대적이점, 호환성, 복잡성을 채택하였고, 조직적 요인에 관한 변수로 최고경영층 지원, 비용부담능력을, 환경적 요인에 관한 변수로는 법적·정책적 지원, 경쟁자 압력을 채택하였다. 이들 3가지 요인에 속한 7가지 변수들과 빅데이터 사용의도와 기대편익 간의 관련성, 그리고 농업벤처 사업분야의 조절효과에 대한 8개의 가설을 설정하였다. 본 연구는 실제 농업벤처기업 종사자 대상 설문을 통한 실증연구를 통해 벤처 현장에서의 빅데이터 활용수준을 높이기 위한 기술적, 조직적, 환경적 관점의 정책 개선방안을 제시하고, 생산/가공/유통 등 사업분야별 비교를 통해 영향요인의 중요도 차이를 규명해 영역별로 차별적이고 효과적인 정책 방향성을 도출하는 데 시사점을 제시하고자 한다.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.236-242
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• 2020

Big data technology has been rising as a leading technology in the healthcare paradigm. As a world-class big data nation including National Health Insurance data, Korea has been focused on health policies and sustainability through database forecasting and policy establishment. So the need for education of big data by public officials in healthcare sector is increasing. However, there has not yet been National Competency Standards(NCS) or education modules, in this study, healthcare big data education module and content have been developed for the public servants with confidence.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

• Land and Housing Review
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• v.7 no.1
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• pp.19-29
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• 2016

This study proposes the big data policy and case studies in Korea and the application of land and housing of spatial big data to excavate the future business and to propose the spatial big data based application for the government policy in advance. As a result, at first, the policy and cases of big data in Korea were evaluated. Centered on the Government 3.0 Committee, the information from each department of government is being established with the big-data-based system, and the Ministry of Land, Infrastructure, and Transport is establishing the spatial big data system from 2013 to support application of big data through the platform of national spatial information and job creation. Second, based on the information system established and administrated by LH, the status of national territory information and the application of land and housing were evaluated. First of all, the information system is categorized mainly into the support of public ministration, statistical view, real estate information, on-line petition, and national policy support, and as a basic direction of major application, the national territory information (DB), demand of application (scope of work), and profit creation (business model) were regarded. After the settings of such basic direction, as a result of evaluating an approach in terms of work scope and work procedure, the four application fields were extracted: selection of candidate land for regional development business, administration and operation of rental house, settings of priority for land preservation, and settings of priority for urban generation. Third, to implement the application system of spatial big data in the four fields extracted, the required data and application and analytic procedures for each application field were proposed, and to implement the application solution of spatial big data, the improvement and future direction of evaluation required from LH were proposed.

• 한국벤처창업학회:학술대회논문집
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• 2019.11a
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• pp.153-155
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• 2019

최근 국내 외를 불문하고 IT기술의 비약적인 발전에 따라 금융분야에서도 금융과 기술이 결합된 새로운 형태의 금융서비스가 다양하게 개발되고 있다. 그러나, 개인금융시장의 비약적 발전에도 불구하고, 기업금융시장에서의 핀테크 활용은 아직까지 미미한 실정이다. 기업 신용평가는 재무제표 위주의 정태적(static) 과거 정보 위주로 이루어지고 있어 업력이 짧고 규모가 영세한 중소기업의 금융접근에 제약이 존재한다. 또한, 중소기업의 인력이 부족한 상황에서 모든 거래를 일일이 금융기관을 방문하여 처리해야 하는 불편함도 애로사항으로 파악되었다. 이러한 한계를 해소하기 위해 신용보증기금은 빅데이터 활용과 비대면 채널에 주목하였다. 본 보고서는 신용보증기금이 빅데이터와 비대면 채널을 활용하여 중소기업의 금융접근성을 향상시킨 사례에 대하여 소개하고자 한다. 첫 번째로, 신보는 기존에 활용되지 못한 동태적(dynamic) 빅데이터를 활용하여 기업의 현재 새로운 신용평가모형을 개발하였다. 두 번째로, 신보는 중소기업의 금융거래 편의성 향상을 위해 비대면 금융업무 플랫폼을 도입하였다. 신보는 이를, 데이터 수집이 체계적이고 정교해야 하며, 중소기업 관련 데이터가 공유되어야 한다는 정책적 시사점을 발견하였다. 이러한 정책적 시사점을 바탕으로 신보는 이제 기업 데이터 뱅크(Data Bank)로서의 역할을 도모하고 있으며, 더 나은 기업정보 생태계를 구현하고자 한다. 이를 통해 신보의 신기술을 활용한 중소기업 금융접근성 제고 사례가 핀테크를 활용한 공공기관의 금융정책 수립에 유용한 사례가 될 수 있을 것으로 기대한다.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.1-16
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• 2024

Over recent years, 6 Sigma has become a key methodology in manufacturing for quality improvement and cost reduction. However, challenges have arisen due to the difficulty in analyzing large-scale data generated by smart factories and its traditional, formal application. To address these limitations, a big data-based 6 Sigma approach has been developed, integrating the strengths of 6 Sigma and big data analysis, including statistical verification, mathematical optimization, interpretability, and machine learning. Despite its potential, the practical impact of this big data-based 6 Sigma on manufacturing processes and management performance has not been adequately verified, leading to its limited reliability and underutilization in practice. This study investigates the efficiency impact of DX SS, a big data-based 6 Sigma, on manufacturing processes, and identifies key success policies for its effective introduction and implementation in enterprises. The study highlights the importance of involving all executives and employees and researching key success policies, as demonstrated by cases where methodology implementation failed due to incorrect policies. This research aims to assist manufacturing companies in achieving successful outcomes by actively adopting and utilizing the methodologies presented.

• Informatization Policy
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• v.23 no.1
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• pp.3-19
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• 2016

The purpose of the study is to analyze the existing literature and to suggest future research directions in the big data security area. This study identifies 62 research articles and analyses their publication year, publication media, general research approach, specific research method, and research topic. According to the results of the analyses, big data security research is at its intial stage in which non-empirical studies and research dealing with technical issues are dominant. From the research topic perspective, the area demonstrates the signs of initial research stage in which proportion of the macro studies dealing with overall issues is far higher than the micro ones covering specific implementation methods and sectoral issues. A few promising topics for future research include overarching framework on big data security, big data security methods for different industries, and government policies on big data security. Currently, the big data security area does not have sufficient research results. In the future, studies covering various topics in big data security from multiple perspectives are anticipated.