Áèçíåñ óïðàâëåíèå

Îùå ñòàòèè îò òîçè áðîé

• 

  METADATA MANAGEMENT FRAMEWORK FOR BUSINESS INTELLIGENCE DRIVEN DATA LAKES

  Data lakes (DL) provide powerful capabilities for processing and utilizing large and diverse data, helping organizations adapt to the modern environment and extract maximum value from the information at their disposal. Effective data analysis provides actionable knowledge which is a competitive advantage for organizations. Metadata management in ... Data lakes (DL) provide powerful capabilities for processing and utilizing large and diverse data, helping organizations adapt to the modern environment and extract maximum value from the information at their disposal. Effective data analysis provides actionable knowledge which is a competitive advantage for organizations. Metadata management in data lakes is a key element in ensuring their full functionality. At the same time, this is a dynamic and under-researched area that reflects the rapid development of information technology and the business needs for effective data management. The research is based on a thorough scientific analysis of existing publications on the chosen topic. For this purpose, up-to-date and relevant open access publications from Scopus and Web of Science that correspond to the keywords "data lake" and "metadata" are identified and are from the last 15 years. Based on a review of the existing literature, the main challenges in data lake metadata management are highlighted. The goal of the research is to summarize the existing models in the field of metadata management in data lakes and to propose a new conceptual framework that can serve as a useful guide for designing and implementing metadata management models in heterogeneous data warehouses, as well as implementation steps. The concept's adoption involves a detailed study of the data management model in a specific organization, a measurement of the level of effectiveness after the model’s implementation, and the use of additional metrics to confirm its feasibility. These tasks are therefore the subject of future research. Another limitation of the proposed framework is that it does not address in depth the rules and standards related to ensuring data security, which would be of the highest priority especially in sectors such as finance, defence and healthcare. In addition, further research could also focus on future analysis of the level of satisfaction with the transformation of metadata management processes.

• 

  THE IMPACT OF REVIEW AND RATING ON CUSTOMER EXPERIENCE IN ELECTRONIC MARKETPLACES

  With the proliferation of e-commerce, online marketplaces have become a dominant platform for consumer purchases. However, the factors driving positive customer experiences in these digital environments remain underexplored. This quantitative study investigates how online reviews and ratings influence customer experience in e-marketplaces. A ... With the proliferation of e-commerce, online marketplaces have become a dominant platform for consumer purchases. However, the factors driving positive customer experiences in these digital environments remain underexplored. This quantitative study investigates how online reviews and ratings influence customer experience in e-marketplaces. A survey was administered to 389 consumers who had made purchases on e-marketplaces in the past six months. Grounded in literature on online consumer behavior, the survey measured relationships between review quantity, review consistency, reviewer expertise, product/service ratings, and customer experience. The results reveal significantly positive impacts of review quantity, consistency, expertise, and ratings on customer experience. As consumers increasingly rely on peer-generated content for purchase decisions, these findings highlight the need for e-marketplace operators to optimize review and rating systems. By empirically demonstrating how online reviews shape the customer experience, this research provides timely insights for platforms, marketers, and policymakers aiming to improve customer satisfaction and loyalty in digital marketplaces. The study contributes to advancing academic understanding of how user-generated content and marketplace design elements interact to drive positive consumer outcomes.

• 

  ADVANTAGES AND ETHICAL CONSIDERATIONS OF INDUSTRIAL IOT ARTIFICIAL INTELLIGENCE SOLUTIONS USAGE

  The objective of this paper is to research the synergistic interaction between Industrial Internet of Things (IIoT) and the application of Artificial Intelligence (AI) in IIoT ecosystems (AIoT). For achieving this purpose, a method of integrative study of leading scientific publications on the topics ‘Industrial Internet of Things’ and ‘Artificial ... The objective of this paper is to research the synergistic interaction between Industrial Internet of Things (IIoT) and the application of Artificial Intelligence (AI) in IIoT ecosystems (AIoT). For achieving this purpose, a method of integrative study of leading scientific publications on the topics ‘Industrial Internet of Things’ and ‘Artificial Internet of Things’ and the PRIZMA flow chart for filtering the list of found documents are applied. The inability of full coverage of the AIoT topic in one article has necessitated the usage of an approach for its content analysis in several thematic groups. The IIoT and AIoT concepts has been explored by various theoretical and practical aspects in many scientific papers published mainly over the past five years, but continues to arouse the interest of researchers. The novelty of the manuscript could be viewed in the attempts of systematizing the key characteristics, advantages, and risks in the practical use of these technologies in the form of smart manufacturing machines, robotic devices, autonomous vehicles, and software for predictive maintenance, and in outlining the possibility for green and sustainable AIoT platforms creation. It is concluded that a key requirement for the implementation of AIoT solutions is the consideration of the various threats and ethical aspects of their design, which contributes to the correct definition of the ‘social value’ of such business initiatives.