• Knowledge Management Research
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• v.14 no.5
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• pp.137-149
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• 2013

Although business Intelligence system is introduced to many companies over the past decade, The result of business benefits from BI investment are not so significant than expected. But still successful BI system can provide the ability to analyse business information in order to support and improve management decision making across a broad range of business activities. In recently, Business Analytics System(BA) is emerging as advanced alternative of outdated and inefficient BI System. This study is focus on constructing procedure of BA system in KB card company, which is major credit card company in South Korea. In practice there were just few works that mentioned well-designed environment of KMS system, and other contribution of this study is to make a platform which invoke revelation of collective intelligence in data analytic professional users group.

• The Korean Journal of Food & Health Convergence
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• v.8 no.6
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• pp.19-29
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• 2022

Business intelligence (BI) is a process for turning data into insights that inform an organization's strategic and tactical decisions. BI aims to give decision-makers the information they need to make better decisions Patient safety analysis, illness surveillance, and fraud identification are just a few healthcare decision-making processes that can be supported by data mining. Thus, the purpose of the current research is to outline the need if BI as an essential factor in the healthcare sector by reviewing various scholarly materials and the findings. The present author conducted one of the most famous qualitative literature approach which has been called as PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement. The selecting criteria for eligible prior studies were estimated by whether studies are suitable for the current research, identifying they are peer-reviewed and issued by notable publishers between 2017 and 2022. According to the result based on the PRISMA analysis, BI plays a vital role in the healthcare sector and there are four business intelligence factors (Data, Analytic, Reporting, and Visualization) that will ensure that the healthcare sector provides the right healthcare services to the customers to be addressed in this section include; data, analytics, reporting, and visualization.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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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.

• Information Systems Review
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• v.17 no.3
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• pp.113-133
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• 2015

In this paper, DEA analysis is employed to compare and evaluate the relative efficiency of a business intelligence (BI) system among five industrial groups such as IT and financial services, electricity and electronics, energy and chemistry, automotive and heavy machinery, and food and apparel. Especially, this study has analyzed the improving tendency of relative efficiency of the industrial groups since they adopted the BI System using Time-Window Analysis. The research findings show that the energy and chemical industry group tends to be remarkably more efficient than the other groups and the electrical and electronic industry turns out to gradually improve their efficiency since the adoption of the BI system.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.45-61
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• 2017

Business intelligence has been attracting much attention these days. Despite such popularity of BI systems, it is widely known that about a half of BI system projects have failed. To grasp why many BI projects end in failure and what factors would make BI projects less failure-prone, a number of BI studies were made to produce a variety of CSFs. However, there is a paucity of information on whether these CSFs are distinctive from those of typical information systems. By identifying how BI CSFs differ from CSFs of typical information systems, we would be able to explain why most BI projects are more likely to be failure. It is believed that a corrective measure about CSFs will lead to more success in future BI projects. In addition, though there have been a number of similar types of BI systems such as decision support systems and executive information systems in existence, there was no study to determine whether there is ever a discrimination between CSFs of BI systems and the similarly-titled systems. This study is to answer these questions using a literature review analysis. The findings of our study are expected to be helpful in a successful implementation of BI systems.

• Journal of Digital Convergence
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• v.11 no.8
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• pp.119-125
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• 2013

The Recently many companies have tried to implement the Business Intelligence (BI) system to enhance the competitive edge in the rapid change of business environment. The BI system is implemented on the basis of current Management Information System, like Enterprise Resource Planning (ERP) system. For the successful implementation of BI system, many critical factors, like maturity and satisfaction level of current Information System, should be considered. The goal of this paper is to analyze which factors influence on the implementation intention of BI system, and how is the relationship among these factors. To achieve this goal, the empirical research has been carried out with factor analysis and Structural Equation Model (SEM). The result of this paper could be usefully referred in decision making process for the successful implementation of the BI system, and show the guideline to the management of the companies, which have the plan for the implementation of BI system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.527-535
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• 2021

Traditional business intelligence (BI) systems have been used widely as tools for better decision-making on time. On the other hand, building a data warehouse (DW) for the efficient analysis of rapidly growing data is time-consuming and complex. In particular, the ETL (Extract, Transform, and Load) process required to build a data warehouse has become much more complex as the BI platform moves to a cloud environment. Various BI solutions based on the NoSQL database, such as MongoDB, have been proposed to overcome these ETL issues. Decision-makers want easy access to data without the help of IT departments or BI experts. Recently, self-service BI (SSBI) has emerged as a way to solve these BI issues. This paper proposes a self-service BI system with farming data using the MongoDB cloud as DW to support the selection of new crops by return-farmers. The proposed system includes functions to provide insights to decision-makers, including data visualization using MongoDB charts, reporting for advanced data search, and monitoring for real-time data analysis. Decision makers can access data directly in various ways and can analyze data in a self-service method using the functions of the proposed system.

• Journal of Information Technology Applications and Management
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• v.24 no.3
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• pp.1-21
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• 2017

Business Intelligence (BI) system is a strategic tool that presents an analytical perspective about business and external environments. Even though its strategic value was well known, users often avoid using it or adopt it ceremonially. In fact, over 50 per cent of BI projects worldwide are reported to end in failure. Such an unexpectedly lower success rate has been a key issue in BI studies. In order to enhance a proper use of information systems, MIS field provided a number of theoretical constructs. One example is Goodhue & Thompson's Task-Technology Fit (TTF). In addition, internalization, the degree to which people make their own effort to modify behavior, was recently suggested as another important determinant of use. Though in MIS community both TTF and internalization proved to be a key determinant of system use, there has been not much study aiming to discover antecedents influencing these constructs. In this study we assert that user participation should be highlighted in BI projects. Especially, we emphasize user participation at the phase of feasibility study that is mainly conducted to determine whether a BI system is essentially necessary and practicable. Our research model employs participative feasibility study as a major antecedent for TTF and internalization that consequently will lead to user satisfaction and actual use. This model was empirically tested on 121 BI system users. The result shows that user participation in feasibility study is positively associated with TTF and internalization, each being related to user satisfaction and system use. It implies that, if an organization has BI users get involved in strategic feasibility study phase, the BI system would turn out to fit users' tasks and, furthermore, users would put more efforts spontaneously in order to use it properly.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.5
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• pp.489-500
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• 2002

As the interest in business interest is increased, data mining is increasingly used in BI as the core technique. To support Business Intelligence in e-business environment, the integrated data mining system which included in various mining operations should be able to flexibly integrate with database system and also it must provide the easy and efficient interface to implement the marketing process in various business applications. In this paper, we have implemented the EC-DaMiner system to support business intelligence in e-business area. The implemented system can be integrated with the conventional database system with the standard interface. Business applications can use MQL mining query language to discover the rules and mining result is modeled in marketing database, and the EC-DaMiner system make the implementation of business marketing process more easy.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.93-98
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• 2012

The rapid change of business environments request the company to act more smart and intelligent in making business strategies and planning the business processes. To meet this requirement, we need to have smart Business Intelligent System(hereinafter "BI") in the company. On the one hand, many korean companies had already installed BI system, and the other hand some companies have plans to implement BI Systems additionally to their Information System. It is very important to have the pictures which factors are critical to the successful implementation of BI, and to survey which critical success factor(hereinafter CSF) are important compared to each factors. In this paper data was gathered from companies already have their BI Systems. We measured IT-Infra maturity, User Education, and Company Organization, and Company Business Strategy, which are the critical success factors for the BI System. After surveying the CSF of BI System, we measured the weights among these factors by AHP. Factor analysis resulted in 6 major factors (Eigenvalue > 1.0), and the AHP analysis showed the list of CSF's weight list according to its significance priorities. The results of this paper could be the valuable references for the implementing process of the BI System in korean company.