Analysis of the impact of big data technologies on the purchasing activities of oil and gas industry enterprises

This paper is devoted to the study of the impact of big data technologies on the purchasing activities of oil and gas industry enterprises. The key aspects of the implementation of big data technologies in the processes of demand planning, inventory management and supplier analysis are considered. Particular attention is paid to the issues of integrating digital tools and methods for big data analysis with existing enterprise information systems (ERP, MES, CRM, SCM). Approaches to demand forecasting are analyzed, including traditional quantitative and qualitative methods, as well as combined approaches that combine both strategies. The application of big data analysis technologies and machine learning to improve the accuracy of forecasts and reduce the risks associated with supplier management is explored. The advantages of multi-agent systems and fuzzy logic methods in selecting reliable suppliers are described. Examples of successful practices of large Russian and international companies, such as BP, Sibur and MMK, are given. The work is aimed at identifying key problems and barriers that arise when implementing big data technologies and suggests ways to overcome them. The results of the study confirm the significant potential of big data technologies for improving procurement activities and increasing the competitiveness of oil and gas companies.