• 디지털융복합연구
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• 제14권5호
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• pp.95-106
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• 2016

본 연구는 빅데이터 유통 생태계에 기반한 단계별 빅데이터 유통 모델 개발 방안을 제안한다. 제안하는 빅데이터 유통모델의 개발은 데이터 중개 및 거래 플랫폼 구축, 거래지원 시스템 구축, 데이터 유통 포털 및 빅데이터 거래소 연결망 구축과 같이 3단계로 구성된다. 데이터 중개 및 거래 플랫폼 구축 단계에서는 데이터 유통 및 거래 플랫폼이 구축되며, 총괄시스템과 등록 및 거래관리 시스템으로 구성되며, 거래지원 시스템 구축 단계에서는 원활한 데이터 거래를 위한 거래지원 시스템이 추가적으로 구축된다. 마지막 데이터 유통 포털 및 빅데이터 거래소 연결망 구축 단계에서는 여러 거래소들의 통합에 필요한 유통 관리 시스템이 구축된다. 새로운 기술, 프로세스, 데이터 과학 등을 이용하여 과거의 데이터 관리 시스템을 빠르게 대체해 나가고 있는 현대의 데이터 시장에서 데이터 유통시장 모델은 계속 진화하고 있으며, 비즈니스 업계에서 수용되고 있다. 따라서 제안하는 빅데이터 유통 모델은 멀지 않은 장래에 데이터를 관리하고 접근하기 위한 산업표준 확립 시 고려될 수 있다고 사료된다.

• 한국항해항만학회지
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• 제46권5호
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• pp.409-417
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• 2022

The International Association of Lighthouse Authorities (IALA) utilizes a questionnaire to investigate the status of Aids to Navigation (AtoN) around the world. However, results of the IALA questionnaire have limited use because respondent understanding is inconsistent. In addition, there is uncertainty regarding the appropriateness of the questionnaire content. Furthermore, the overall response rate is low. Therefore, the status of AtoN is not clearly understood. AtoN data from around the world are generated hourly. Thus, big data solutions are required to effectively exploit the information. Digitization of analog data is an important component of building big data. Hence, the IALA has developed a Maritime Resource Name (MRN) scheme and an information exchange standard. Here, we used the AtoN information exchange standard and designed an S-201-based big data construction process that could collect and manage global AtoN information. In this study, construction of an IALA AtoN portal was proposed as the core of the construction of the AtoN big data. The process was divided into three stages. IALA AtoN portal is developed by IALA with the goal to provide various meaningful statistical analysis results based on AtoN data while managing AtoN information around the world based on S-201. If an AtoN portal capable of constructing S-201-based big data is developed, then a data collection and storage system that can gather basic S-201 AtoN data from the IALA and global AtoN management agencies could be achieved. Furthermore, insightful statistical analysis of AtoN status worldwide and changes in manufacturing technology will be possible.

• 디지털산업정보학회논문지
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• 제12권4호
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• pp.51-58
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• 2016

In the area of hotel and tourism sector, various research are analyzed using big data. Big data is being generated by any digital devices around us all the times. All the digital process and social media exchange produces the big data. In this paper, we analyzed the de-identification method of big data to use the personal information of hotel guests. Through the analysis of these big data, hotel can provide differentiated and diverse services to hotel guests and can improve the service and support the marketing of hotels. If the hotel wants to use the information of the guest, the private data should be de-identified. There are several de-identification methods of personal information such as pseudonymisation, aggregation, data reduction, data suppression and data masking. Using the comparison of these methods, the pseudonymisation is discriminated to the suitable methods for the analysis of information for the hotel guest. Also, among the pseudonymisation methods, the t-closeness was analyzed to the secure and efficient method for the de-identification of personal information in hotel.

• The Journal of Asian Finance, Economics and Business
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• 제10권2호
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• pp.15-27
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• 2023

The purpose of this research is to investigate the impact of Business Intelligence (BI) on the relation between Big Data Analytics (BDA) and Financial Performance (FP), at the beginning we reviewed the academic accounting and finance literature to develop the theoretical framework of business intelligence, big data and financial performance in terms of definition, motivations and theories, then we conduct an empirical analysis based on questionnaire-base survey data collected. The researchers identified the study population in the joint-stock companies listed on the Egyptian Stock Exchange and operating in the sectors and activities related to modern technologies in information systems, big data analytics, and business intelligence, in addition to the auditing offices that review the financial reports of these companies, and The sector closest to the research objective is the communications, media, and information technology sector, where the survey list was distributed among the sample companies with (15) lists for each company, and (15) lists for each audit office, so that the total sample becomes (120) individuals (with a response rate 83.3%), The results show, First, Big data analytics significantly affect organizations' financial performance, second, Business intelligence mediates (partial) the relationship between big data analytics and financial performance.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 추계학술대회
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• pp.89-91
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• 2017

환율은 국가 화폐들 간의 교환 비율로 국가 경제 규모 또는 현황을 측정하기 위한 주요 지표 중 하나이다. 환율은 다양한 경제 또는 인문사회 활동에 의하여 영향을 받으며 시간에 따라 유동적으로 변화하는 특성을 가진다. 그러나 너무 많은 경제, 인문사회 활동 요소들이 환율에 영향을 주며 각 요소들의 영향력이 매우 유동적이기 때문에 특정 활동 요소와 환율 변동성과의 관계를 정의하기 어려운 문제가 있다. 이 논문에서는 환율 변동성과 활동 요소들과의 관련성을 살펴보기 위하여 신문 기사와 환율 변동성과의 데이터 패턴 분석을 한다. 일정 기간 동안의 신문 기사에서 단어들의 출현 빈도를 조사하고 환율 변동 폭과 비교한다.

• Journal of Information Processing Systems
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• 제20권3호
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• pp.391-398
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• 2024

Given the further promotion of economic globalization, China's financial market has also expanded. However, at present, this market faces substantial risks. The main financial and economic risks in China are in the areas of policy, credit, exchange rates, accounting, and interest rates. The current status of China's financial market is as follows: insufficient attention from upper management; insufficient innovation in the development of the financial economy; and lack of a sound financial and economic risk protection system. To further understand the current situation of China's financial market, we conducted a questionnaire survey on the financial market and reached the following conclusions. A comprehensive enterprise questionnaire from the government's perspective, the enterprise's perspective and the individual's perspective showed that the following problems exist in the financial and economic risk prevention aspects of big data and Internet of Things in China. The political system at the country's grassroots level is not comprehensive enough. The legal regulatory system is not comprehensive enough, leading to serious incidents of loan fraud. The top management of enterprises does not pay enough attention to financial risk prevention. Therefore, we constructed a financial and economic risk prevention model based on big data and Internet of Things that has effective preventive capabilities for both enterprises and individuals. The concept reflected in the model is to obtain data through Internet of Things, use big data for screening, and then pass these data to the big data analysis system at the grassroots level for analysis. The data initially screened as big data are analyzed in depth, and we obtain the original data that can be used to make decisions. Finally, we put forward the corresponding opinions, and their main contents represent the following points: the key is to build a sound national financial and economic risk prevention and assessment system, the guarantee is to strengthen the supervision of national financial risks, and the purpose is to promote the marketization of financial interest rates.

• International journal of advanced smart convergence
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• 제13권3호
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• pp.135-142
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• 2024

Recently, along with digital transformation, technologies such as cloud computing, big data, and artificial intelligence have been actively introduced. In a situation where these technological changes are progressing rapidly, it is often difficult to manage processes efficiently using existing simple workflow management methods. Companies providing current cloud services are adopting virtualization technologies, including virtual machines (VMs) and containers, in their distributed system infrastructure for automated application deployment. Accordingly, this paper proposes a process-based orchestration system for integrated execution of corporate process-oriented workloads by integrating the potential of big data and machine learning technologies. This system consists of four layers as components for performing workload processes. Additionally, a common information model is applied to the data to efficiently integrate and manage the various formats and uses of data generated during the process creation stage. Moreover, a standard metadata protocol is introduced to ensure smooth exchange between data. This proposed system utilizes various types of data storage to store process data, metadata, and analysis models. This enables flexible management and efficient processing of data.

• 정보보호학회논문지
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• 제32권1호
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• pp.141-154
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• 2022

데이터 경제시대 속에서 활발한 데이터 유통환경을 조성하고자 다양한 정책들이 시행되고 있다. 국내에서는 공공주도 데이터 거버넌스 아래 금융데이터거래소의 출범을 시작으로 빅데이터 유통 플랫폼 형성과 데이터 거래가 시작되었다. 주요 데이터 선진국들의 경우, 오래전부터 데이터브로커 산업을 바탕으로 데이터 유통환경을 구축해왔고, 그로부터 산출되는 부가가치들을 통해 국가 데이터 경쟁력을 강화해왔다. 그런데 데이터브로커를 통해 이루어지는 활발한 데이터 유통의 이면에는 수많은 정보보호 이슈들이 존재하고, 이로 인해 다양한 프라이버시 문제와 국가 안보적 위협들이 발생하였다. 이러한 문제들은 국내 금융데이터 거래 과정에서도 충분히 발생할 수 있다. 본 연구에서는 데이터브로커로 인해 발생한 데이터 거래의 정보보호 이슈를 살펴보고, 정보보호의 관점에서 데이터 거래 시 고려해야 할 사항들을 도출하였다. 이후, 정보보호 고려사항들이 국내 금융데이터거래소 거래단계별 정보보호 정책에 잘 반영되어 있는지 검증해보았다. 이를 바탕으로 금융데이터거래의 정보보호 강화방안을 제시하였다.

• 디지털융복합연구
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• 제14권12호
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• pp.591-597
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• 2016

타당한 연구 수행을 위해서는 방법론이 중요하다. 소셜네트워크서비스로부터 수집되는 데이터를 대상으로 하는 소셜 빅데이터 연구는 최근 들어 새롭게 부각되는 연구이지만 아직 이에 합당한 연구방법이 충분하지 않은 실정이다. 이에 본 연구에서는 소셜 빅데이터 분석에 합당한 연구방법론 개발에 앞서, 연구문제의 설정에 대하여 체계적으로 정리하고 질문의 기본 유형을 제시하고자 한다. 그리고 제시되는 6가지 기본 유형에 따른 데이터 형태를 살펴보고자 한다. 나아가 SNS로부터 수집되는 빅데이터 분석과 관련된 통계적인 제 문제에 대해서도 고찰해 보도록 하겠다. 본 연구의 결과는 향후 관련 연구자들이 데이터 유형에 맞는 올바른 연구문제를 수립하고 분석함으로써 타당한 정보를 도출하는데 도움이 될 것으로 사료된다.

• Journal of Information Processing Systems
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• 제13권6호
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• pp.1575-1584
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• 2017

As interest in big data has increased recently, NoSQL, a solution for storing and processing big data, is getting attention. NoSQL supports high speed, high availability, and high scalability, but is limited in areas where data integrity is important because it does not support multiple row transactions. To overcome these drawbacks, many studies are underway to support multiple row transactions in NoSQL. However, existing studies have a disadvantage that the number of transactions that can be processed per unit of time is low and performance is degraded. Therefore, in this paper, we design and implement a multi-row transaction system for data integrity in big data environment based on HBase, a column-based NoSQL which is widely used recently. The multi-row transaction system efficiently performs multi-row transactions by adding columns to manage transaction information for every user table. In addition, it controls the execution, collision, and recovery of multiple row transactions through the transaction manager, and it communicates with HBase through the communication manager so that it can exchange information necessary for multiple row transactions. Finally, we performed a comparative performance evaluation with HAcid and Haeinsa, and verified the superiority of the multirow transaction system developed in this paper.