Business Intelligence and Big Data for Innovative, Collaborative and Sustainable Development of Organizations in Digital Era

Permanent URI for this collectionhttps://hdl.handle.net/10125/107401

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    Business Intelligence Fog IoT node development model for Big Data processing of air quality in scientific partnerships
    (2024-01-03) Behrens, Grit; Karatzas, Kostas; Orlowski, Cezary
    The aim of the current paper is to present a dynamic model of managing nodes of the Fog layer in Edge-Fog-Cloud systems of the Internet of Things in scientific partnerships. The article is a response to the problem of managing Fog nodes in IoT systems, where classic management mechanisms, based on schedules, become insufficient. It also addresses the problem of delays in data processing in the Cloud layer, which is significant and affects decision-making processes. Therefore, the authors propose a Business Intelligence model based on association rules that predict the number of agents of Fog layer nodes. This prediction allows for the design of nodes in which the requirements of the scientific partner (number of processor cores, RAM size, classifier type, number of processed records, classifier working time) are the basis for selecting the appropriate number of Fog node agents. The model was validated by using association rules to select the appropriate number of Fog node agents for the domain of air quality data processed in three scientific partnerships using different types of data classifiers.
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    Exploring the Benefits, Challenges, and Opportunities of Collaborative Business Intelligence
    (2024-01-03) Weichbroth, Paweł; Zurada, Jozef; Olszak, Celina
    In traditional business intelligence (BI) settings, the collective decision-making process is often hindered by the absence of knowledge and expertise exchange among various stakeholders, as well as lack of information sharing. The study delves into the concept of Collaborative BI, which aims to overcome these limitations by promoting collaboration, business networking, knowledge sharing, and improved communication among stakeholders. Based on a systematic literature review, the study explores the notion of Collaborative BI, formulates its definition, and reports on its challenges, benefits, and limitations. It also provides an insightful overview of Collaborative BI landscape and multiple advantages it can deliver to modern business organizations. The study also acknowledges potential threats to the validity of its findings due to the limited scope of the literature review. Finally, the study highlights the need for further research to address the limitations and expand our understanding of the CBI field.
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