Research on the application of big data technology in enterprise digital transformation

Ruiwen Ma; Chang Hao

doi:10.1117/12.3006454

26 September 2023 Research on the application of big data technology in enterprise digital transformation

Ruiwen Ma, Chang Hao

Proceedings Volume 12793, International Conference on Mechatronics and Intelligent Control (ICMIC 2023); 127930V (2023) https://doi.org/10.1117/12.3006454
Event: International Conference on Mechatronics and Intelligent Control (ICMIC2023), 2023, Wuhan, China

Abstract

Big data technology as the foundation of the construction and development of modern society, according to the huge data information and diversified processing technology, technology innovation in each field provides technical support. Whether in the domestic environment or in the international environment, digital transformation has become the preferred strategic decision goal of the industry development, among which the unique advantages of large enterprises are very obvious. By understanding the management principles put forward by enterprise development and integrating big data technology to realize the goal of enterprise digital transformation, it can not only improve the business processing capacity and stabilize the basic assets, but also provide strong support for enterprise strategic planning. Therefore, based on understanding the concept of big data technology and the present situation of enterprise digital transformation, this article, based on the analysis of enterprise digital transformation path based on the big data, deeply studies how Chinese commercial banks apply the theory of big data technology in enterprise digital transformation.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ruiwen Ma and Chang Hao "Research on the application of big data technology in enterprise digital transformation", Proc. SPIE 12793, International Conference on Mechatronics and Intelligent Control (ICMIC 2023), 127930V (26 September 2023); https://doi.org/10.1117/12.3006454

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