Opportunities and Barriers to Using Big Data Technologies in the Metallurgical Industry

Abstract

One of the key areas of digital transformation of modern metallurgical production, which involves a high degree of automation as well as the use of complex technological systems, is the adaptation of production and business processes to new IT technologies for collecting and processing information. The purpose of this work is to study the conditions and business prospects for using big data technologies to improve the efficiency of production and operational activities of metallurgical enterprises in the context of digital transformation. The article examines the problems and prospects of using big data analysis tools to obtain significant economic results in an enterprise, considers the main barriers to the introduction of big data technologies in the industry and ways to overcome them, and analyses the results of the implementation of technologies for the construction of big data platforms of the data lake class at metallurgical enterprises in Russia. The results of the study show that the use of machine learning technologies and predictive analytics tools based on big data platforms could have a significant impact on reducing operating costs, increasing labour productivity, and improving the efficiency of metallurgical production.