• Title/Summary/Keyword: Big Data

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A Study on the Effect of Organization's Environment on Acceptance Intention for Big Data System (빅데이터 시스템의 수용의도에 영향을 미치는 수용조직의 환경요인에 관한 연구)

  • Kim, Eun Young;Lee, Jung Hoon;Seo, Dong Ug
    • Journal of Information Technology Applications and Management
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    • v.20 no.4
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    • pp.1-18
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    • 2013
  • Big data has become a worldwide topic. Despite this, big data accurately understand and acquire the business to take advantage of companies that were only very few. The purpose of this study is to investigate the factors that effect Korean firm's adopting big data system. Empirical test was conducted to verify hypotheses using extended technology acceptance model and we analyzed factors which affect the behavioral intention of big data System. Based upon previous researches, we have selected organization innovation, organization slank, organization information system infra maturity, perceived benefits of big data system, perceived usefulness, perceived ease of use, behavioral intention as variables and proposed a research model based on survey questionnaires. From those, we drew that perceived usefulness and perceived ease of use influenced the behavioral intention. The results of this study will increase the users' awareness on big data system and contribute to develop a way to enable the introduction of new technologies.

The Key Factors of Big Data Utilization for Improvement of Management Quality of Companies in terms of Technology, Organization and Environment (기술, 조직, 환경 관점에서 기업의 경영품질 향상을 위한 빅데이터 활용의 핵심요인에 관한 연구)

  • Shin, Soo Haeng;Lee, Sang Joon
    • Journal of Information Technology Services
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    • v.18 no.1
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    • pp.91-112
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    • 2019
  • The IoT environment has led to explosive growth of existing enterprise data, and how to utilize such big data is becoming an important issue in the management field. In this paper, major factors affecting the decisions of companies to utilize big data have been studied. And also, the effect of big data utilization on the management quality is studied empirically. During this process, we have studied the difference according to the award of Korean national quality award. As a result of the study, we confirmed that the five factors such as cost from technology, organization and environment perspective, compatibility, company size, chief officer support, and competitor pressure are key factors influencing big data utilization. Also, it was confirmed that the use of big data for management activities has an important influence on the six management quality factors based on MBNQA, and that the management quality level of Korean national quality award companies is relatively high. This paper provides practical implications for companies' use of big data because it demonstrates for the first time that big data utilization has an impact on management quality improvement.

Analysis of Traffic Card Big Data by Hadoop and Sequential Mining Technique (하둡과 순차패턴 마이닝 기술을 통한 교통카드 빅데이터 분석)

  • Kim, Woosaeng;Kim, Yong Hoon;Park, Hee-Sung;Park, Jin-Kyu
    • Journal of Information Technology Applications and Management
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    • v.24 no.4
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    • pp.187-196
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    • 2017
  • It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object-Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

Research on the Analysis System based on the Big Data for Matlab (Matlab을 활용한 빅데이터 기반 분석 시스템 연구)

  • Joo, Moon-il;Kim, Hee-cheol
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.96-98
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    • 2016
  • Recently, big data technology develop due to the rapid data generation. Thus big data analysis tools for analyzing big data has been developed. Typical big data tools are the R program, Hive, Tajo and more. But data analysis based on Matlab is still common used. And it is still used in big data analysis. In this paper, it research into big data analysis system based on the Matlab for analyzing vital signals.

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a Study on Using Social Big Data for Expanding Analytical Knowledge - Domestic Big Data supply-demand expectation - (분석지의 확장을 위한 소셜 빅데이터 활용연구 - 국내 '빅데이터' 수요공급 예측 -)

  • Kim, Jung-Sun;Kwon, Eun-Ju;Song, Tae-Min
    • Knowledge Management Research
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    • v.15 no.3
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    • pp.169-188
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    • 2014
  • Big data seems to change knowledge management system and method of enterprises to large extent. Further, the type of method for utilization of unstructured data including image, v ideo, sensor data a nd text may determine the decision on expansion of knowledge management of the enterprise or government. This paper, in this light, attempts to figure out the prediction model of demands and supply for big data market of Korea trough data mining decision making tree by utilizing text bit data generated for 3 years on web and SNS for expansion of form for knowledge management. The results indicate that the market focused on H/W and storage leading by the government is big data market of Korea. Further, the demanders of big data have been found to put important on attribute factors including interest, quickness and economics. Meanwhile, innovation and growth have been found to be the attribute factors onto which the supplier puts importance. The results of this research show that the factors affect acceptance of big data technology differ for supplier and demander. This article may provide basic method for study on expansion of analysis form of enterprise and connection with its management activities.

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A Study on a Way to Utilize Big Data Analytics in the Defense Area (국방분야 빅데이터 분석의 활용가능성에 대한 고찰)

  • Kim, Seong-Woo;Kim, Gak-Gyu;Yoon, Bong-Kyu
    • Journal of the Korean Operations Research and Management Science Society
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    • v.39 no.2
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    • pp.1-19
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    • 2014
  • Recently, one of the core keywords in information technology (IT) as well as areas such as business management is big data. Big data is a term that includes technology, personnel, and organization required to gather/manage/analyze collection of data sets so large and complex that it becomes difficult to manage and analyze using traditional tools. The military has been accumulating data for a long period due to the organization's characteristic in placing emphasis on reporting and records. Considering such characteristic of the military, this study verifies the possibility of improving the performance of the military organization through use of big data and furthermore, create scientific development of operation, strategy, and support environment. For this purpose, the study organizes general status and case studies related to big data, traces back examples of data utilization by Korean's national defense sector through US military data collection and case studies, and proposes the possibility of using and applying big data in the national defense sector.

Fishery R&D Big Data Platform and Metadata Management Strategy (수산과학 빅데이터 플랫폼 구축과 메타 데이터 관리방안)

  • Kim, Jae-Sung;Choi, Youngjin;Han, Myeong-Soo;Hwang, Jae-Dong;Cho, Wan-Sup
    • The Journal of Bigdata
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    • v.4 no.2
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    • pp.93-103
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    • 2019
  • In this paper, we introduce a big data platform and a metadata management technique for fishery science R & D information. The big data platform collects and integrates various types of fisheries science R & D information and suggests how to build it in the form of a data lake. In addition to existing data collected and accumulated in the field of fisheries science, we also propose to build a big data platform that supports diverse analysis by collecting unstructured big data such as satellite image data, research reports, and research data. Next, by collecting and managing metadata during data extraction, preprocessing and storage, systematic management of fisheries science big data is possible. By establishing metadata in a standard form along with the construction of a big data platform, it is meaningful to suggest a systematic and continuous big data management method throughout the data lifecycle such as data collection, storage, utilization and distribution.

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Anonymity Personal Information Secure Method in Big Data environment (빅데이터 환경에서 개인정보 익명화를 통한 보호 방안)

  • Hong, Sunghyuck;Park, Sang-Hee
    • Journal of Convergence for Information Technology
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    • v.8 no.1
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    • pp.179-185
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    • 2018
  • Big Data is strictly positioning one of method to deal with problems faced with mankind, not an icon of revolution in future anymore. Application of Big Data and protection of personal information have contradictoriness. When we weight more to usage of Big Data, someone's privacy is necessarily invaded. otherwise, we care more about keeping safe of individual information, only low-level of research using Big Data can be used to accomplish public purpose. In this study, we propose a method to anonymize Big Data collected in order to investigate the problems of personal information infringement and utilize Big Data and protect personal. This will solve the problem of personal information infringement as well as utilizing Big Data.

Trends of Big Data and Artificial Intelligence in the Fashion Industry (빅데이터와 인공지능을 중심으로 한 패션산업의 동향)

  • Kim, Chi Eun;Lee, Jin Hwa
    • Journal of the Korean Society of Clothing and Textiles
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    • v.42 no.1
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    • pp.148-158
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    • 2018
  • This study analyzes recent trends in fashion retailing instigated by the fourth industrial revolution and approaches the trends in terms of the convergence of big data and artificial intelligence. The findings are as below. First, companies like 'Edited' and 'Stylumia' offer solutions that support the strategic decisions of fashion brands and fashion retailers by analyzing big data using artificial intelligence. Second, the convergence of big data and artificial intelligence scales personalized service on the web as examples of 'Coded Couture', 'StitchFix', and 'Thread'. Third, the insights gained from artificial intelligence and big data help create new fashion retailing platforms such as 'Botshop' and 'Lyst'. Last, artificial intelligence and big data assist with design. 'Ivyrevel' designs digital fashion, assisted by a macroscopic perspective on fashion trends, market and consumers through the analysis of big data. The Fourth Industrial Revolution brings changes across all industries that will likely accelerate. The fashion industry is also undergoing many changes with advancements in scientific technology. The convergence of big data and artificial intelligence will play a key role in the future of fast-moving industry like fashion, where fickle tastes of consumers are the main drivers.

Application Analysis of Smart Tourism Management Model under the Background of Big Data and IOT

  • Gangmin Weng;Jingyu Zhang
    • Journal of Information Processing Systems
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    • v.19 no.3
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    • pp.347-354
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    • 2023
  • The rapid development of information technology has accelerated the application of big data and the Internet of Things in various industries. Big data has a great potential in the development of smart tourism. With the help of innovation in emerging technologies such as big data and Internet of Things, smart tourism has a better possibility to surpass traditional tourism. Therefore, this article provides a theoretical support to this process. It has explored the innovative management model of big data and IoT in smart tourism and evaluate their effects on promoting tourism. It offers a reference for the integration and innovation of the tourism theory system. Before big data technology, the development of Internet boosted online tourism. However, tourism marketing is still inefficient due to a lack of understanding about tourists. After many practical explorations of big data technology, tourism websites begin to adopt big data technology in their daily operations. With the changes in tourists' preferences and needs, further innovation and research are needed to help smart tourism keep up with the changes in the market and create more competitive products and services. Innovation serves as the driving force for enterprises to occupy the market and develop.