• 산업경영시스템학회지
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• 제42권4호
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• pp.84-90
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• 2019

Lately, there have been tremendous shifts in the business technology landscape. Advances in cloud technology and mobile applications have enabled businesses and IT users to interact in entirely new ways. One of the most rapidly growing technologies in this sphere is business intelligence, and associated concepts such as big data and data mining. BI is the collection of systems and products that have been implemented in various business practices, but not the information derived from the systems and products. On the other hand, big data has come to mean various things to different people. When comparing big data vs business intelligence, some people use the term big data when referring to the size of data, while others use the term in reference to specific approaches to analytics. As the volume of data grows, businesses will also ask more questions to better understand the data analytics process. As a result, the analysis team will have to keep up with the rising demands on the infrastructure that supports analytics applications brought by these additional requirements. It's also a good way to ascertain if we have built a valuable analysis system. Thus, Business Intelligence and Big Data technology can be adapted to the business' changing requirements, if they prove to be highly valuable to business environment.

• 한국전자거래학회지
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• 제7권1호
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• pp.141-152
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• 2002

Data dictionary is a collection of meta-data, which describes data produced and consumed while performing business processes. Data dictionary is an essential element for business process standardization and automation, and has a fundamental role in ERP application management and customization. Also, data dictionary facilitates B2B processes by enabling painless integration of business processes between various enterprises. We implemented data dictionary support in SEA＋, a component- based scalable ERP system developed in ETRI, and found out that it's a plausible feature of business information system. We discovered that data dictionary promotes semantic, not syntactic, data management, which can make it possible to leverage viability of the tool in the coming age of more meta-data oriented computing world. We envision that business data dictionary is a firm foundation of adapting business knowledge, applications and processes into the semantic web based enterprise infra-structure.

• 대한안전경영과학회지
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• 제13권2호
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• pp.231-241
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• 2011

Business processes are often of long duration, and include internal worker's decision making, which makes business processes to be exposed to many exceptional situations. These properties of business processes makes it difficult to guarantee successful termination of business processes at the design phase. The behavioral properties of business processes mainly depends on the data aspects of business processes. To formalize the data aspect of process modeling, this paper proposes a graph-based model, called Data Dependency Graph (DDG), constructed from dependency relationships specified between business data. The paper also defines a mechanism of describing a set of mapping rules that generates a process model semantically equivalent to a DDG, which is accomplished by allocating data dependencies to component activities.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제57차 동계학술대회논문집 26권1호
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• pp.31-34
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• 2018

We live in the digital era, and the characteristics of our customers in the digital era are constantly changing. That's why understanding business requirements and converting them to technical requirements is essential, and you have to understand the data model behind the business layout. Moreover, BI(Business Intelligence) is at the crux of revolutionizing enterprise to minimize losses and maximize profits. In this paper, we have described a leading study about the situation of desk-top BI(software product & programming language) in aspect of front-end side and the Data Lake platform based on Big Data by data modeling in aspect of back-end side to support the business intelligence.

• 한국전자거래학회지
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• 제15권4호
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• pp.79-99
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• 2010

e-비즈니스의 활성화로 기업과 조직에서 이해당사자 간의 데이터 교환이 활발해 짐에 따라, 신뢰성 있는 데이터의 확보 및 관리가 시급한 과제로 떠오르고 있다. 이러한 문제를 해결하기 위해, 본 논문은 데이터의 품질을 체계적으로 관리할 수 있는 프레임워크를 시나리오와 함께 제시한다. 데이터 품질 관리 프레임워크는 데이터 품질 모니터링, 데이터 품질 개선, 데이터 활용의 3단계로 구분되어 있으며 각 단계마다 3개씩, 총 9개의 프로세스로 구성되어 있다. 각 프로세스에는 필요성, 기능, 역할, 프로세스간의 관계가 명시되어 있다. 또한, 본 프레임워크를 현장에 직접 적용할 수 있도록, e-비즈니스에서 많이 사용되는 상품식별 및 분류 코드체계의 사례를 이용하여 업무 시나리오를 제시하였다.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2011년도 춘계학술대회
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• pp.329-338
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• 2011

Business processes are often of long duration, and include internal worker's decision making, which makes business processes to be exposed to many exceptional situations. These properties of business processes makes it difficult to design processes to support uncertainties from internal or external environments. The behavioral properties of business processes mainly depends on the data aspects of business processes. To formalize the data aspect of process modeling, this paper proposes a graph-based model, called Data Dependency Graph (DDG), constructed from dependency relationships specified between business data. The paper also defines a mechanism of describing a set of mapping rules that generates a process model semantically equivalent to a DDG, which is accomplished by allocating data dependencies to component activities.

• International Journal of Computer Science & Network Security
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• 제24권7호
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• pp.177-185
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• 2024

Web science, a general discipline of learning is presently at high demand of expertise with ideas to develop software-based WebApps and MobileApps to facilitate user or customer demand e.g. shopping etc. electronically with the access at their smartphones benefitting the business enterprise as well. A worldwide-computerized reservation network is used as a single point of access for reserving airline seats, hotel rooms, rental cars, and other travel related items directly or via web-based travel agents or via online reservation sites with the advent of social-web, e-commerce, e-business, from anywhere-on-earth (AoE). This results in the accumulation of large and diverse distributed databases known as big data. This paper describes a novel intelligent web-based electronic booking framework for e-business with distributed computing and data mining support with the detail of e-business system flow for e-Booking application architecture design using the approaches for distributed computing and data mining tools support. Further, the importance of business intelligence and data analytics with issues and challenges are also discussed.

• 아태비즈니스연구
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• 제15권1호
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• pp.131-143
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• 2024

Purpose - The purpose of this study was to analyze cases of big data-driven business in the financial industry, focusing on organizational structure and business processes using big data in banking industry. Design/methodology/approach - This study used a case study approach. To this end, cases of two banks implementing big data-driven business were collected and analyzed. Findings - There are two things in common between the two cases. One is that the central tasks for big data-driven business are performed by a centralized organization. The other is that the role distribution and work collaboration between the headquarters and business departments are well established. On the other hand, there are two differences between the two banks. One marketing campaign is led by the headquarters and the other marketing campaign is led by the business departments. The two banks differ in how they carry out marketing campaigns and how they carry out big data-related tasks. Research implications or Originality - When banks plan and implement big data-driven business, the common aspects of the two banks analyzed through this case study can be fully referenced when creating an organization and process. In addition, it will be necessary to create an organizational structure and work process that best fit the special situation considering the company's environment or capabilities.

• 융합보안논문지
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• 제16권4호
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• pp.3-15
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• 2016

비즈니스 데이터란 회사 업무 진행 과정 중에 생성, 저장, 이용, 전달되는 모든 온오프라인 형태의 문서 및 전자적 데이터를 의미하며, 영업, 조직, 매출, 마케팅, 배송 관련된 모든 데이터를 의미한다. 대부분의 회사에는 사내 문서 생성 및 보안 관리 가이드에 의거하여 비밀, 대외비의 등급은 이미 존재하나, 실제 사용하고 있는 비즈니스 데이터를 상세히 분석하여 반영할 수 있는 의사결정 기준 수립이 미흡하다. 본 논문에서는 비즈니스 데이터를 분류할 수 있는 정성적, 정량적인 기준(평가 지표)을 수립하기 위한 비즈니스 데이터 decision matrix를 설계할 수 있는 방안을 제시하고, 각 등급별로 보호할 수 있는 기준을 제시해보고자 한다.

• 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.