Research Article
Enterprise Big Data Management and Analysis System Based on Cloud Computing
@INPROCEEDINGS{10.4108/eai.19-5-2023.2334413, author={Yicai Li and Yehong Li}, title={Enterprise Big Data Management and Analysis System Based on Cloud Computing}, proceedings={Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19--21, 2023, Hangzhou, China}, publisher={EAI}, proceedings_a={ICBBEM}, year={2023}, month={7}, keywords={cloud computing; big data; enterprise crisis; management system}, doi={10.4108/eai.19-5-2023.2334413} }
- Yicai Li
Yehong Li
Year: 2023
Enterprise Big Data Management and Analysis System Based on Cloud Computing
ICBBEM
EAI
DOI: 10.4108/eai.19-5-2023.2334413
Abstract
In a large information environment, business problems are characterized by high reliability, uncertainties, and informational difficulties. Response ability has exceeded the ability of enterprises to manage them. In order to solve this problem, this article presents a design idea for emergency management system based on cloud computing technology in large data environment. It analyzes the main operation modes of the disaster management cloud platform, including LAS, PaaS, and SaaS, to meet the complex disaster management in large data environment. Using the advantage of cloud computing platform to achieve enterprise information crisis management can help enterprises to obtain timely and accurate information, and reduce the cost of decision-making problem. Cooperative crisis management of large groups under large information circumstances is a complex interactive decision-making process. The process of pushing for information resolution and providing authorization for crisis management, as well as mechanisms for demobilization, coordination, and crisis management, the evaluation and elimination mechanism of crisis response risks, and the feedback and negotiation mechanism of disposal results are the problems that need to be solved in the crisis management decision support system under big data.