Proceedings of the 2020 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020)

Innovation of Enterprise Financial Management Model Under the Background of Big Data

Authors
Liangcan Liu, Lulin Li
Corresponding Author
Lulin Li
Available Online 2 November 2020.
DOI
10.2991/assehr.k.201030.063How to use a DOI?
Keywords
big data, enterprise financial management, opportunities and challenges, mode innovation
Abstract

With the continuous development of science and technology, the rapid popularization and wide application of the Internet and smart terminals, data has shown explosive growth, and the emergence of massive data heralds the arrival of the era of big data. The theory and practice of enterprise financial management aiming at creating value must fully consider and proactively respond to the challenges and changes brought by big data to enterprises, so as to seek better development space for enterprises. This article discusses the characteristics and functions of financial management, the opportunities and challenges faced, and how to innovate financial management models.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2020 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
2 November 2020
ISBN
10.2991/assehr.k.201030.063
ISSN
2352-5398
DOI
10.2991/assehr.k.201030.063How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Liangcan Liu
AU  - Lulin Li
PY  - 2020
DA  - 2020/11/02
TI  - Innovation of Enterprise Financial Management Model Under the Background of Big Data
BT  - Proceedings of the 2020 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020)
PB  - Atlantis Press
SP  - 307
EP  - 312
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201030.063
DO  - 10.2991/assehr.k.201030.063
ID  - Liu2020
ER  -