빅데이터의 주요 활용사례

김용겸 동중앙아시아경상학회 2016 동중앙아시아연구 Vol.27 No.1

본 연구는 빅데이터에 대한 세계 주요 국가의 주요 활용사례에 대한 연구이다. 외국의 주요 활용사례는 북미(127 개), 유럽(38개), 아시아태평양(28개, 호주와 뉴질랜드를 포함) 지역 순으로 나타났다. 소개된 외국의 국가(UN, EU 제외)는 24개국이며, 미국의 경우 가장 많은 126개의 활용사례가 소개되었다. 세계 주요 국가의 주요 활용사례 관련 분야는 총 35개 분야인데, 이 중에서 비즈니스 분야가 80개를 차지하여 가장 많이 소개되었다. 비즈니스 분야(21개 분야로 세분류화)에서는 마케팅(광고 및 추천서비스 등)이 23번으로 가장 많이 소개되었다. 우리나라의 주요 활용사 례를 보면, 소개된 기관의 수는 103개이며 SK텔레콤이 7번으로 가장 많이 소개되었다. 주요 활용사례 관련분야는 총 27개 분야인데 분류된 분야는 외국의 경우와 대동소이하였으며, 외국의 경우와 같이 비즈니스 분야가 60개를 차지하여 가장 많이 소개되었다. 비즈니스 분야(15개 분야로 세분류화)에서는 마케팅(광고 및 추천서비스 등)이 20번 으로 가장 많이 소개되었는데, 외국의 경우와 비교해 볼 때 순위상 차이가 있다(마케팅과 고객만족 분야는 각각 1위 와 2위를 차지하여 동일함). 결론부분에서는 본연구의 한계점과 향후 주요 과제 및 정책방향을 언급하였다. The radical increase of data means that it needs a new paradigm to analyze such big data in relation to new opportunity. The ability to deal with big data has evolved as a mainstream in IT, Statistics, Business Management, and others. Big data has drawn huge attention from researchers and practitioners in government and enterprises. The study is aimed to demonstrate about big data utilization cases including big data concept, related technology, analysis method, and others. Especially, the study will focus on the main utilization cases of major countries of big data from various papers, books, newspapers, websites, and others. Broad variety of big data utilization cases have been developed in foreign countries and Korea. The foreign utilization cases such as North America(127), Europe(38), Asia Pacific region(28) were mentioned. The number of mentioned foreign country were 24, the number of utilization cases of United States were 126(the most utilization cases among mentioned countries). The number of classified fields of utilization cases were 35 and utilization cases of business were 80(the most mentioned classified fields). In business that was subdivided into 21 classified fields, marketing(advertising and referral services, etc.) was mentioned 23 times. In Korean utilization cases, the number of mentioned organization were 103 and SK Telecom was the most up to 7 times. The number of classified fields of utilization cases were 27 and business was the most mentioned fields account for 60. In business that was subdivided into 15 classified fields, marketing(advertising and referral services, etc.) was mentioned 20 times. But overal ranking were different between foreign countries and Korea except marketing and customer satisfaction fields when compared with foreign cases. In conclusion the researcher mentioned that the limitations and key challenges and policy directions of the research.

물류 빅데이터 구축 실태 및 활용사례 분석을 통한 활성화 방안

신나라 ( Nala Shin ),김용진 ( Yong Jin Kim ) 한국물류학회 2018 물류학회지 Vol.28 No.2

본 논문에서는 4차산업혁명을 이끄는 요소기술로서 각광받고 있는 빅데이터 기술을 물류분야에 접목시켜서 활성화 할 수 있는 방안을 찾고자 한다. 이를 위하여 우선 빅데이터의 기술적 정의를 살펴보고 국내외 기술동향을 분석하였다. 이후 우리나라의 공공분야에서 수집관리하고 있는 물류관련 빅데이터를 조사 분석하였다. 이와 함께 해외의 공공분야 물류 빅데이터 구축상황을 조사분석하고 국내사례와 비교하여 시사점을 도출하였다. 그리고 기업이 주도하고 있는 민간분야의 국내외 물류 빅데이터 활용실태를 조사하였다. 이를 바탕으로 시사점을 도출하고 물류 빅데이터 활성화에 대한 법제도적 애로요인을 분석하여 개인정보보호법, 빅데이터 공개방식, 빅데이터 원천관리 등 개선방안을 제시하였다. In this paper, we try to find a way to combine Big Data technologies that are leading The Fourth Industrial Revolution into logistics. To that end, we first investigated technical definitions of big data and analyzed the technical trends at South Korea and advanced countries. After that, this paper shows variety types of data collected and managed by South Korea’s governmental institutions, which have a great possibility to be aggregated as Big Data. Along with that, we investigated overseas success cases of Big Data applications in logistics fields and provided comparative analysis between domestic cases and foreign cases. This paper also examines current utilization status of Big Data technologies in the field of logistics led by private sectors. Based on findings, we suggested ways to make betterments for a practical application of Big Data technologies. These suggestions include elaborating Personal Information Protection Act, deep considerations on a varied methods of data release, and an advanced management tool for handling Big Data sources.

Exploration on the New Legal Discovery Model of China's Smart Judiciary

张光君,张翔 중국지역학회 2022 중국지역연구 Vol.9 No.3

In the process of promoting the upgrading of judicial intelligence, in order to realize the transformation of the effect of adjudication from “visible justice”―“expressing justice”― “acceptable justice”, the Supreme People’s Court of China proposed a new model of legal application based on the “retrieve system for similar cases” and supported by “brain-like intelligence technology”. However, due to the lack of innovation in legal methodology adapted to the big data of similar cases, judges still make legal discovery and “legal interpretation and reasoning” based on the small data. However, the wisdom of the legal community extracted on the basis of big data is difficult to have a substantial impact on the judge’s testimony from the level of legal methods. This makes the retrieval system of similar cases into a “chicken rib”. In order to fundamentally reverse the current problems of unclear methods of legal discovery and the ineffectiveness of the retrieval system for similar cases, it is urgent to stimulate the potential of big data technology. That is to say, through the transformation of the underlying thinking paradigm, a new mode of legal discovery is constructed, and then the efficiency of the retrieval system for similar cases is fully released. This paper adheres to the theory of “technology-institutional co-evolution” and follows the approach of “What (meaning of new legal discovery)-Why (value of new legal discovery)-How (implementation of new legal discovery)”. At the same time, this paper adopts the research methods such as the comparison of the principles of legal discovery in the two legal systems and the empirical analysis of the normative documents of the judiciary. The new model of legal discovery is based on the retrieval system of similar cases. After realizing the intelligent identification of similar cases with the help of big data, the “common factors” of similar cases are extracted through the comparison of types. Then, through the two-way communication between the abstract norm and the pending facts, the process realizes the finalization of specific specifications within the scope of the semantic range of the abstract norm. This model is conducive to unifying the standards for the application of the law and facilitates the same judgment in similar cases. In order to implement this model and improve the level of intellectualization in legal discovery, the main body of the retrieval report for similar cases should be changed from “the judge's individual combat” to “the coordinated attack of the judge + judge's assistant + lawyer”. After reducing unnecessary restrictions on starting conditions, the search is carried out for all valid cases. Next, the process of judging the similarity of similar cases is included in the presentation content of the retrieval report of similar cases. At the same time, the ranking of similar cases is based on “similarity of similar cases”, supplemented by “level of effectiveness”.

국내 금융기관의 빅 데이터(Big Data)활용 사례에 관한 연구

서민교(Min Kyo Seo) 중앙대학교 한국전자무역연구소 2013 전자무역연구 Vol.11 No.4

최근 세계적으로 데이터의 양이 폭발하고 있기 때문에 거대한 자료 즉, 빅데이터를 분석하는 것이 주목을 받고 있으며 빅데이터는 향상된 인사이트(Insight)와 더 나은 의사결정을 위해 사용되는 비용 효율이 높고, 혁신적인 형태의 정보를 요구하는 대용량ㆍ고속 및 다양성의 특성을 가진 정보자산이다. 국내외 금융기관들도 빅데이터를 적극 활용하고 있다. 본 연구에서는 국내 금융기관을 대상으로 빅데이터의 도입사례를 분석한 후 빅데이터의 효과적인 활용을 위한 시사점을 제시하였으며, 구체적인 시사점으로 선진 금융기관들의 빅데이터 활용사례의 분석 필요, 전략 로드맴 하의 빅데이터의 도입, 기술ㆍ시스템ㆍ인력 등 빅데이터 활용 역량 강화, 빅데이터 관련 법적 규제 모니터링 및 대응 필요 등을 제시하였다. Recently, as the amount of data in the world has been exploding, analyzing large data - so called Big Data - will become a hot issue. Big Data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information for enhanced insight and decision making. Domestic and foreign banking institutions make the most of Dig Data. The purpose of this paper is to the contribute to utilize the use of Big data for Korean financial institutions by investigating the case study on the current status and problems of the Big Data in Korean financial institutions. Based on the results, improvements measures for utilizing use of Big Data in Korean financial institutions are derived. And several implications for policy makers are provided.

Approach to Big Data-based Reference Architecture for Specific Use Cases

안철범,김진홍 한국지식정보기술학회 2021 한국지식정보기술학회 논문지 Vol.16 No.6

Recently, according to increase big data utilization, it keeps going on a various research their area. In spite of big data and the corresponding technologies being already widespread, many big data projects do fail or do not deliver the promised results. Hence, we proposed the specific case in the insurance sector and our approach is about to one reason with respective projects. But, it does not take into account or analyze the business value of a specific big data use case, and this uses a different approach by analyzing the business aspects of use cases in the insurance sector. A number of possible use cases in insurance is derived from a literature study. Then these use cases are evaluated in expert interviews in order to find out, which ones do have the highest potential. Eventually, based on these requirements and a comparison of existing Reference Architectures for big data in common, a new reference architecture is designed for big data in insurance. Accordingly, the final goal is to use this reference architecture as a blueprint for deriving components in order to implement big data use cases in insurance. The reference architecture is proposed in a case study by designing a solution architecture for specific use cases.

4차 산업혁명시대의 빅데이터 정보자원 관리전략에 관한 연구

고형석,이홍제,임화연,한경석 한국엔터프라이즈아키텍처학회 2018 정보기술아키텍처연구 Vol.15 No.2

미래의 4차산업혁명시대에서 가장 중요한 정보자원으로 관리해야 하는 대상으로 데이터는 빠지지 않을 것이다. 빅데이터는 데이터 가치를 파악하고, 데이터를 활용하게 하는 확실한 방안이지만, 빅데이터를 준비하는 단계부터 빅데이터를 관리하기 위한 전략이 필요하다. 왜냐하면, 빅데이터는 많은 정보자원을 도입해야 사용이 가능하기 때문에 체계적으로 정보자원을 관리해야한다. 정보자원을 효율적으로 관리해서 조직목표 달성에 기여하는 것이 정보자원 관리의 목적이다. 다양하고 복잡한 빅데이터 정보자원 관리를 위한 도구로 범정부 EA활용에서 착안하였다. 빅데이터 사례를 EA관점에서 분석하면서 정보자원 관리기준과 체계로서 EA를 검증하였다. EA는 정보자원 관리도구로 충분하다는 연구결과를 도출하였다. 빅데이터 등 새로운 정보자원 관리의 전략으로서 EA를 제안한다. Data is the most important information resource in the future industrial revolution era. Big Data is a clear way to understand data values and leverage data, but strategies are needed to manage Big Data from the start of preparing Big Data. Because Big Data requires a lot of information resources to be introduced so that it needs to be systematically managed. The strategy of information resource management is to manage information resources efficiently and to contribute to achieving organizational goals. It was inspired by the use of government-governed EA as a tool for managing diverse and complex Big Data information resources. In analyzing the Big Data case from an EA perspective, EA was validated as an information resource management criteria and framework. EA has derived research results that are sufficient with information resource management tools. It proposes EA as a strategy for managing new information resources such as Big Data.

농생명산업의 빅데이터 실용사례에 대한 분석과 활용 방안

박로운,김현,송미장 한약정보연구회 2015 한약정보연구회지 Vol.3 No.3

The purpose of this study is to suggest the meaning, application and utilization of big data for developing in agroindustry through the analysis on the home and abroad cases about the utilization of big data in agroindustry. The practiced cases were investigated by searching on the portal sites using keywords such as agroindustry and big data. As a result, abroad cases of big data are the following as Monsanto's FieldScripts, JohnDeere‘s SeedStar Mobile, DuPont Pioneer’s Pioneer Field360 Select of USA, Phytech software of Israel, Silent herdsman’s Cattle Health Care Management System of Scotland, Integrated Management Control System of EU, Flower Trade System of Netherlands, Fujitsu's Cow Step Counts System, Smartagri System, and FARMS Case of Japan. In home cases are the following as Smart green house, Apple cultivation, Tomato farmers Internet of Things (loT), Strawberry cultivation systems, and Integrated management system of direct transactions in the local food. The case of ubiquitous farm are under the development. Consequently, utilization of big data in agroindustry is to contribute significantly to activate the economy of local economy, as well as the effect of cost reduction for production of agricultural products.

무역 디지털 트랜스포메이션을 위한 빅데이터 도입 및 활용에 관한 연구

정준모,정윤세 한국무역학회 2022 貿易學會誌 Vol.47 No.3

The process and change of convergence in the economy and industry with the development of digital technology and combining with new technologies is called Digital Transformation. Specifically, it refers to innovating existing businesses and services by utilizing information and communication technologies such as big data analysis, Internet of Things, cloud computing, and artificial intelligence. Digital transformation is changing the shape of business and has a wide impact on businesses and consumers in all industries. Among them, the big data and analytics market is emerging as one of the most important growth drivers of digital transformation. Integrating intelligent data into an existing business is one of the key tasks of digital transformation, and it is important to collect and monitor data and learn from the collected data in order to efficiently operate a data-based business. In developed countries overseas, research on new business models using various data accumulated at the level of government and private companies is being actively conducted. However, although the trade and import/export data collected in the domestic public sector is being accumulated in various types and ranges, the establishment of an analysis and utilization model is still in its infancy. Currently, we are living in an era of massive amounts of big data. We intend to discuss the value of trade big data possessed from the past to the present, and suggest a strategy to activate trade big data for trade digital transformation and a new direction for future trade big data research.

공공데이터를 활용한 맞춤형 여행 네비게이션 시스템 구현

심범수 ( Beomsoo Shim ),이한준 ( Hanjun Lee ),유동희 ( Donghee Yoo ) 한국인터넷정보학회 2016 인터넷정보학회논문지 Vol.17 No.1

최근 정부는 창조경제라는 패러다임에 따라 다양한 분야의 공공데이터를 개방하고 여러 종류의 대국민 서비스를 구축하는 등 공공데이터 활용을 통한 가치창출에 역점을 두고 있다. 본 논문에서는 여행에 관한 공공데이터와 사용자 정보를 융합하여 사용자에게 맞춤형 여행 정보를 추천하는 시스템을 구현하였다. 본 시스템에서는 사례기반추론(CBR) 방식을 이용하여 사용자별 맞춤형 정보 추천이 가능하도록 하였다. 본 시스템은 사용자 중심의 여행 정보를 제공한다는 측면에서 기존의 여행 시스템들과 차별화된다고 할 수 있으며, 턴키(Turn-key) 방식의 콘텐츠 제공으로 사용자의 편의성을 극대화할 수 있는 유용한 도구로 활용될 수 있을 것으로 판단 된다. 본 연구가 공공데이터의 성공적인 활용 사례가 되기를 기대한다. Under the flag of creative economy, Korea government is now releasing public data in order to develop or provide a range of services. In this paper, we develop a customized trip navigation system to recommend a trip itinerary based on integration of open government data and personal tourist data. The system uses case-based reasoning (CBR) to provide a personalized trip navigation service. The main difference between existing trip information systems and ours is that our system can offers a user-oriented information service. In addition, our system supports Turn-key style contents provision to maximize convenience. Our system can be a good example of the way in which open government data can be used to design a new service.

Big Data Analysis: Managerial Applications, Taxonomy, and Cases

최무진 한국로고스경영학회 2011 로고스경영연구 Vol.9 No.3

The amount of information created and distributed, due to advanced IT and expanding zones of mobile devices, has exponentially increased in recent years. Therefore, many corporations are collecting a large amount of data through sensors, either software- or hardware-based, but lack appropriate analytical tools and strategic guidance in using them. This paper focuses on managerial issues companies may face as an era of ‘Big Data' becomes a reality in a business sector. Specifically, first, this paper addressed why an analytical capability will be another core competence of corporations in super competitive business environments. Then six managerial applications of Big Data analysis were described with supportive short cases. Finally, we proposed a taxonomy that can be used to understand BDA cases in a more theoretical perspective, and subsequently 3 categories of cases were described.