Design and Implementation of Information Management System for Enterprise Decision Support

In today’s rapidly changing business environment, enterprise decision support systems are important tools for improving organizational decision-making efficiency and effectiveness. This paper explores designing and implementing an information management system for enterprise decision support. The system relies on modern information technology and integrates multiple functions such as data processing, model analysis, and intelligent decision-making, providing strong data support and decision recommendations for managers. Firstly, the paper analyzes the common problems encountered in the decision-making process of enterprises and the necessity of information systems for decision support. Subsequently, the structural design of the information management system was described in detail, including key technical components such as data warehouse, online analytical processing, and data mining. The system implementation section explains how to use relational database management systems and business intelligence tools to build an efficient and flexible decision support platform. Finally, the application effect of the system in enterprise decision-making was demonstrated through a practical case, and the positive role played by the information management system in optimizing enterprise decision-making was concluded. The practice has proven that this system can significantly improve the quality of enterprise decision-making and provide the impetus for sustainable growth of enterprises.

Authors

Institutions

Publication Details

Journal
SHS Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/shsconf/202521301002
Primary Topic
Information Technology Governance and Strategy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design and Implementation of Information Management System for Enterprise Decision Support

Yuxuan Han, Y. Zhang, Yining Chen
SHS Web of Conferences
Information Technology Governance and Strategy
article

Design and Implementation of Information Management System for Enterprise Decision Support

Yuxuan Han, Y. Zhang, Yining Chen
article en

Abstract

In today’s rapidly changing business environment, enterprise decision support systems are important tools for improving organizational decision-making efficiency and effectiveness. This paper explores designing and implementing an information management system for enterprise decision support. The system relies on modern information technology and integrates multiple functions such as data processing, model analysis, and intelligent decision-making, providing strong data support and decision recommendations for managers. Firstly, the paper analyzes the common problems encountered in the decision-making process of enterprises and the necessity of information systems for decision support. Subsequently, the structural design of the information management system was described in detail, including key technical components such as data warehouse, online analytical processing, and data mining. The system implementation section explains how to use relational database management systems and business intelligence tools to build an efficient and flexible decision support platform. Finally, the application effect of the system in enterprise decision-making was demonstrated through a practical case, and the positive role played by the information management system in optimizing enterprise decision-making was concluded. The practice has proven that this system can significantly improve the quality of enterprise decision-making and provide the impetus for sustainable growth of enterprises.

SHS Web of ConferencesVol. 213
Baoding University (CN)
Openalex Percentile: Top 92%
Information Technology Governance and Strategy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.