Please use this identifier to cite or link to this item: https://repository.hneu.edu.ua/handle/123456789/37117
Title: The impact of big data analytics on the effectiveness of management decisions
Authors: Zelenyi D.
Keywords: information processing
forecasting
algorithmic approaches
process optimisation
artificial intelligence
Issue Date: 2025
Publisher: ХНЕУ ім. С. Кузнеця
Citation: Zelenyi D. The impact of big data analytics on the effectiveness of management decisions / D. Zelenyi // Управління розвитком. – 2025. – Т. 24, № 2. – С. 20-30.
Abstract: The aim of the study was to assess the impact of big data analytics on the quality of managerial decisions by analysing key technologies, data processing methods, and data interpretation in the modern business environment. The research methodology included the analysis and comparison of existing approaches to the use of big data analytics in various industries, as well as the application of case study and modelling methods to evaluate the impact of big data on the effectiveness of managerial decisions under conditions of unstable resource provision. The study also analysed the practical use of big data in finance, marketing, logistics, manufacturing, human resource management, and public administration based on real cases from companies such as Amazon, Uber, Walmart, General Electric, and Netflix. Types of machine learning algorithms (classification, clustering, regression, deep learning), examples of the application (customer segmentation, demand forecasting, anomaly detection), and the impact on the effectiveness of managerial decisions were described. Key technologies were outlined – Hadoop, Spark, and Tableau – which ensured the processing, analysis, and visualisation of big data. Emphasis was placed on the advantages of big data – improved forecasting accuracy, personalisation, automation, market adaptation – and the challenges of implementation, particularly the need for computational resources, qualified personnel, and data protection, which were critical for achieving managerial efficiency. The results obtained will allow enterprises to optimise operational processes, increase the efficiency of resource use, and adapt strategic decisions to specific market conditions and technological challenges. Furthermore, the study made it possible to improve the integration of big data analytics with other digital technologies, such as BIM and IoT, which contributed to more accurate forecasting and optimisation of business processes. The practical value of the study lies in identifying ways to effectively apply big data analytics to improve managerial decisions in various sectors.
URI: https://repository.hneu.edu.ua/handle/123456789/37117
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