Abstract
Objective: to characterize the features and prospects of using big data tools and technologies in the management of the transportation process on railways. Methods: neural network modeling, system analysis, forecasting, programming, big data, predictive analytics. Results: a datalogical model of entities for storing up-to-date data on cargo flows is proposed, and a structure for building a system for accumulating information is proposed. In addition, the paper examines the applied issues of solving the problems of storing, receiving and processing data using big data methods. Practical significance: Improving the management of railway transportation processes in the context of digital transformation in terms of obtaining more accurate forecasts.
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