• Title/Summary/Keyword: Big-data Management

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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.

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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Challenges and Opportunities of Big Data

  • Khalil, Md Ibrahim;Kim, R. Young Chul;Seo, ChaeYun
    • Journal of Platform Technology
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    • v.8 no.2
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    • pp.3-9
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    • 2020
  • Big Data is a new concept in the global and local area. This field has gained tremendous momentum in the recent years and has attracted attention of several researchers. Big Data is a data analysis methodology enabled by recent advances in information and communications technology. However, big data analysis requires a huge amount of computing resources making adoption costs of big data technology. Therefore, it is not affordable for many small and medium enterprises. We survey the concepts and characteristics of Big Data along with a number of tools like HADOOP, HPCC for managing Big Data. It also presents an overview of big data like Characteristics of Big data, big data technology, big data management tools etc. We have also highlighted on some challenges and opportunities related to the fields of big data.

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A Study on Efficient Building Energy Management System Based on Big Data

  • Chang, Young-Hyun;Ko, Chang-Bae
    • International journal of advanced smart convergence
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    • v.8 no.1
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    • pp.82-86
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    • 2019
  • We aim to use public data different from the remote BEMS energy diagnostics technology and already established and then switch the conventional operation environment to a big-data-based integrated management environment to operate and build a building energy management environment of maximized efficiency. In Step 1, various network management environments of the system integrated with a big data platform and the BEMS management system are used to collect logs created in various types of data by means of the big data platform. In Step 2, the collected data are stored in the HDFS (Hadoop Distributed File System) to manage the data in real time about internal and external changes on the basis of integration analysis, for example, relations and interrelation for automatic efficient management.

Big Data Governance Model for Smart Water Management (스마트 물관리를 위한 빅데이터 거버넌스 모델)

  • Choi, Young-Hwan;Cho, Wan-Sup;Lee, Kyung-Hee
    • The Journal of Bigdata
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    • v.3 no.2
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    • pp.1-10
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    • 2018
  • In the field of smart water management, there is an increasing demand for strengthening competitiveness through big data analysis. As a result, systematic management (Governance) of big data is becoming an important issue. Big data governance is a systematic approach to evaluating, directing and monitoring data management, such as data quality assurance, privacy protection, data lifetime management, data ownership and clarification of management rights. Failure to establish big data governance can lead to serious problems by using low quality data for critical decisions. In addition, personal privacy data can make Big Brother worry come true, and IT costs can skyrocket due to the neglect of data age management. Even if these technical problems are fixed, the big data effects will not be sustained unless there are organizations and personnel who are dedicated and responsible for data-related issues. In this paper, we propose a method of building data governance for smart water data management based on big data.

A Study on Demand-Side Resource Management Based on Big Data System (빅데이터 기반의 수요자원 관리 시스템 개발에 관한 연구)

  • Yoon, Jae-Weon;Lee, Ingyu;Choi, Jung-In
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.8
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    • pp.1111-1115
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    • 2014
  • With the increasing interest of a demand side management using a Smart Grid infrastructure, the demand resources and energy usage data management becomes an important factor in energy industry. In addition, with the help of Advanced Measuring Infrastructure(AMI), energy usage data becomes a Big Data System. Therefore, it becomes difficult to store and manage the demand resources big data using a traditional relational database management system. Furthermore, not many researches have been done to analyze the big energy data collected using AMI. In this paper, we are proposing a Hadoop based Big Data system to manage the demand resources energy data and we will also show how the demand side management systems can be used to improve energy efficiency.

A study on the Effect of Big Data Quality on Corporate Management Performance (빅데이터 품질이 기업의 경영성과에 미치는 영향에 관한 연구)

  • Lee, Choong-Hyong;Kim, YoungJun
    • Journal of the Korea Convergence Society
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    • v.12 no.8
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    • pp.245-256
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    • 2021
  • The Fourth Industrial Revolution brought the quantitative value of data across the industry and entered the era of 'Big Data'. This is due to both the rapid development of information & communication technology and the diversity & complexity of customer purchasing tendencies. An enterprise's core competence in the Big Data Era is to analyze and utilize the data to make strategic decisions for enterprise. However, most of traditional studies on Big Data have focused on technical issues and future potential values. In addition, these studies lacked interest in managing the quality and utilization levels of internal & external customer Big Data held by the entity. To overcome these shortages, this study attempted to derive influential factors by recognizing the quality management information systems and quality management of the internal & external Big Data. First of all, we conducted a survey of 204 executives & employees to determine whether Big Data quality management, Big Data utilization, and level management have a significant impact on corporate work efficiency & corporate management performance. For the study for this purpose, hypotheses were established, and their verifications were carried out. As a result of these studies, we found that the reasons that significantly affect corporate management performance are support from the management class, individual innovation, changes in the management environment, Big Data quality utilization metrics, and Big Data governance system.

A Study on Big Data Analytics Services and Standardization for Smart Manufacturing Innovation

  • Kim, Cheolrim;Kim, Seungcheon
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.3
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    • pp.91-100
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    • 2022
  • Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.

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.

A Study on the Strategy of the Use of Big Data for Cost Estimating in Construction Management Firms based on the SWOT Analysis (SWOT분석을 통한 CM사 견적업무 빅데이터 활용전략에 관한 연구)

  • Kim, Hyeon Jin;Kim, Han Soo
    • Korean Journal of Construction Engineering and Management
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    • v.23 no.2
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    • pp.54-64
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    • 2022
  • Since the interest in big data is growing exponentially, various types of research and development in the field of big data have been conducted in the construction industry. Among various application areas, cost estimating can be a topic where the use of big data provides positive benefits. In order for firms to make efficient use of big data for estimating tasks, they need to establish a strategy based on the multifaceted analysis of internal and external environments. The objective of the study is to develop and propose a strategy of the use of big data for construction management(CM) firms' cost estimating tasks based on the SWOT analysis. Through the combined efforts of literature review, questionnaire survey, interviews and the SWOT analysis, the study suggests that CM firms need to maintain the current level of the receptive culture for the use of big data and expand incrementally information resources. It also proposes that they need to reinforce the weak areas including big data experts and practice infrastructure for improving the big data-based cost estimating.