A medical organization is a complex body comprising different units and processes which unequivocally pose dilemmas related to hospital management. In this study, we summarize the requirements ...emerging from hospital indicators as they relate to medical management and propose a new architecture that can effectively support these requirements. The most important characteristics of this indicator based BI (BI) system are: (1) indicator data collection automation, (2) demonstration of a simplified BI key performance indicator (KPI) model using the Taiwan Quality Indicator (TQIP ) project, (3) provision of a convenient and effective graphical user interface, and (4) support for outer feedback information being rejoined into a Data Warehouse for indicator comparison analysis.
In this study, three models were empirically compared, the DeLone and McLean model, the Seddon model and the Modified Seddon model, by measuring the impact of a business intelligence system (BIS) in ...companies in Peru. After that, the mediators and dependent constructs were analysed to determine if they were behaving properly (a good level of variance explanation and significant relations with others constructs). The study used a sample of 104 users of the BIS, from companies in several important economic sectors, in a quasi-voluntary context and with six constructs: information quality, system quality, service quality, system dependence (system use), user satisfaction and perceived usefulness (individual impact). Design/methodology/approach To interpret the results, the authors used structural equations. The idea was to look for the best fit and explanations for the outcomes. The main difference in these models is that the DeLone and McLean model considers system dependence (system use) as a part of information system success, but in the Seddon model, it is a consequence of it. Findings The Seddon model seems to show the best fit and explanation for the outcomes. After that, a review of the system use construct was realised, because of its limited variance explained and the few significant relations with other constructs, to improve its explanation power in future research. Research limitations/implications It is estimated that the sample includes more than 15 per cent of all the companies that use a BISs in Peru, so the size of the sample is adequate, but it is not entirely random and therefore limits the generalizability of outcomes. Besides that, a sample size that is bigger could be better for the sake of making a more detailed analysis, permitting the use of some items with less power, or the use of another statistical procedure for structural equations such as the Asymptotical Distribution Free, permitting a more detailed analysis (Hair et al., 2006). Originality/value Business intelligence (BI), one of the most important components of information systems (IS), is playing a very relevant role in business in this time of high competition, high amounts of data and new technology. Currently, companies feel pressured to respond quickly to change and complicated conditions in the market, needing to make the correct tactical, operational and strategic decisions (Chugh and Grandhi, 2013). BI is one of the most important drivers of the decade (Gartner, 2013). Big companies of IS are creating special units specialised in BI, helping companies become more efficient and effective in daily operations.
R Bakery company is a company that produces bread every day. Products that produced in that company have many different types of bread. Products are made in the form of sweet bread and wheat bread ...which have different tastes for every types of bread. During the making process, there were defects in the products which the defective product turns into reject product. Types of defects that are produced include burnt, sodden bread and shapeless bread. To find out the information about the defects that have been produced then by applying a designed model business intelligence system to create database and data warehouse. By using model business Intelligence system, it will generate useful information such as how many defect that produced by each of the bakery products. To make it easier to obtain such information, it can be done by using data mining method which data that we get is deep explored. The method of data mining is using k-means clustering method. The results of this intelligence business model system are cluster 1 with little amount of defect, cluster 2 with medium amount of defect and cluster 3 with high amount of defect. From OLAP Cube method can be seen that the defect generated during the 7 months period of 96,744 pieces.
Background: Despite increasing importance of the use of Business Intelligence (BI) as a technology-driven process for giving decision support, the success or failure of BI has not been investigated ...fully in South Africa. BI is not well understood because of an absence of documented proof of its practice.Objectives: This study was intended to investigate BI and identify the moderating and mediating effects of user satisfaction on the relationship between system quality, information quality and service quality on the one hand and perceived net benefits on the other in South Africa.Methods: The quantitative methods approach was predominantly used in this study. A total of 211 responses were obtained from a random sample of 250 BI users throughout South Africa. A semi-structured online survey questionnaire was used to collect the data, and correlation and multiple regression analyses were used to analyse it.Results: It was found that user satisfaction mediates the relationship between perceived net benefits and system quality and service quality. It also moderates the effects of system quality and service quality on perceived net benefits. Information quality is not related with user satisfaction and perceived net benefits.Conclusion: The implication of the results is that system quality and user satisfaction should be enhanced and maintained to achieve perceived positive net benefits in order to make the BI system more effective and efficient.
Most of the information collected in different fields by Instituto de Investigación Biomédica de A Coruña (INIBIC) is classified as unstructured due to its high volume and heterogeneity. This ...situation, linked to the recent requirement of integrating it to the medical information, makes it necessary to implant specific architectures to collect and organize it before it can be analysed. The purpose of this article is to present the Hadoop framework as a solution to the problem of integrating research information in the Business Intelligence field. This framework can collect, explore, process and structure the aforementioned information, which allow us to develop an equivalent function to a data mart in an Intelligence Business system.
The election decision-making process is very complex, whether to voters or to political
parties. The integration of business intelligence into this process may become one of the
key elements that ...support and improve the election decision-making process. This research
paid special attention to the integration of business intelligence into such a process. It is
inspired by the IMC model and based on cloud computing. This structural concept offers a
definition to the four important levels of decision. These levels take into account the
maximum number of factors that may influence the success of an election process.
Le processus de décision électoral est un processus complexe. Que se soit pour les électeurs, ou bien pour les partis politiques. L’intégration de l’informatique décisionnelle dans ce processus peut devenir une clé importante, qui peut offrir un appui et une amélioration aux décisions électorales. La présente investigation a mis une attention particulière sur l’intégration de l’informatique décisionnelle dans le processus électoral. Inspiré du modèle IMC, et basé sur l’informatique nuageuse. La présente conception architecturale propose la définition de quarte importants niveaux décisionnels. Ces niveaux tiennent en compte le maximum de facteurs qui peuvent influencer la réussite du processus décisionnel électoral.
Business intelligence is a collection of methodologies, methods, architectures, and technologies that convert raw data into significant and useful information used by organizations to enable more ...effective strategic, tactical, and operational insights and decision-making. In spite of several studies have examined the critical success factors and development of business intelligence System, but few relevant studies have investigated perceptions of end-users Business Intelligence Systems. Furthermore, none of those studies was performed in a Higher Education Sector in Iraq. Consequently, the study aims to determine the business intelligence system features influencing perceived impact end users’ and of using business intelligence systems in Iraqi educational institutes. A technology acceptance model and technology organization environment framework were syntheses as a basis to develop a research model for business intelligence users' perceived impact and adopt of business intelligence systems named (SMUPI-BIS). Later, an online instrument (questionnaire) was designed to gather data from the business intelligence system users in five Iraqi universities. Twenty-one hypotheses were proposed and later tested. Then, for data analysis, the authors used several methods such as hierarchical regression, one-way ANOVA, descriptive statistics as well as structural equation modeling (SEM). The main outcomes of this study suggest that decision support, information quality, and real-time reporting are the most significant system characteristics influencing end users' perceived impact and their usage of business intelligence systems.
In the current data-driven era, businesses continuously generate vast quantities of data, underscoring the critical importance of deriving actionable insights from this data deluge to inform ...decision-making. Despite the potential of Business Intelligence (BI) tools, a noticeable gap persists. Most existing BI tools require extensive customization for non-technical users, posing barriers to accessing and comprehending essential business metrics. This paper introduces a novel self-service business intelligence (BI) system that utilizes the Python programming language. The system aims to address the existing gap in the field. The system places emphasis on several key factors, including ease of use, flexibility in data formatting, preprocessing capabilities, relevancy of data insights, and the inclusion of a user-friendly interface. The evaluation process dif-fers from the traditional approach by including a direct comparison with the widely recognized software Microsoft Power BI. Encouragingly, our findings indicate a significant enhancement in the user experience for non-technical users. This affirms the effectiveness and usability of our system in facilitating more informed decision-making. The Python-based solution we have developed enables individuals without technical expertise to effectively engage with, examine, and extract valuable insights from intricate datasets, while circumventing the generally challenging learning process associated with business intelligence (BI) technologies. As we collectively navigate the data-driven environment, our endeavors contribute to the improvement of the accessi-bility and usability gap within the domain of business intelligence.
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