scholarly journals Design of Enterprise Economic Information Management System Based on Big Data Integration Algorithm

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Xiao Liu

In economic growth, the gradual increase in the effect of information technology makes the enterprise economic information management increasingly important for the survival and development of the enterprises. This paper designs an enterprise economic information management system for the complex internal economic information management business and process of enterprises. It provides daily office, information access, document preview, and transmission. The proposed design (i) copes with the inconsistency and irregularity of enterprise economic information data, (ii) quickly obtains valuable information from these massive high-frequency data, and (iii) improves the economic benefits of data assets and data management efficiency. The printing function systematizes the information management for departments such as enterprise economic information, personnel, and production. The main focus of this research includes the mode, framework, and function of the whole system software. Moreover, it also comprises of the use of Internet platform big data technology to realize the practicality, stability, and security of the system database algorithm, which has been practically used by enterprises to improve office efficiency and meet the needs of daily management of enterprises. Based on the analysis of the current status of enterprise big data application, this paper constructs an enterprise economic informational management system based on big data and also describes in detail the key technologies of enterprise economic informational data management from three aspects: NoSQL-based big data storage management, Hadoop-based economic informational big data informational and economic informational big data analysis, and mining algorithm. Provide theoretical basis and basic technical support for online decision analysis.

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yu Jiang ◽  
Hang Yu ◽  
Jun Jiang

Schizophrenia is a serious mental disease whose pathogenesis has not been fully elucidated. Its clinical evaluation and diagnosis still highly depend on the clinical experience of doctors. It is of great scientific value and clinical significance to study the inducing factors and neuropathological mechanism of schizophrenia. Based on the four research problems of schizophrenia, this paper analyzes the data types that need to be stored in clinical trials and scientific research, including basic information, case report data, neuropsychological and cognitive function evaluation, magnetic resonance data, electroencephalogram (EEG) data, and intestinal flora data. Through the demand analysis of the system, including the data management part, data analysis part, the functional demand of the system management part, and the overall nonfunctional demand of the system, the overall architecture design, functional module division, and database table structure design of the system are completed. Adopting Browser/Server (B/S) architecture and front-end and back-end separation mode and applying Java and Python programming language, based on spring framework and database, a multidimensional information management system for schizophrenia is designed and implemented, which includes four modules: data analysis, data management, system management, and security control. In addition, each functional module of the system is designed and implemented in detail, and the software operation flow of each module is illustrated with the sequence diagram. Finally, the multidimensional data of schizophrenia collected in our laboratory were used for system test to verify whether the system can meet the needs of clinical big data management of schizophrenia and the multidimensional information management system of schizophrenia can meet the needs of clinical big data management. The information management system helps schizophrenic researchers to carry out data management and data analysis. It also has advantages that are easy to use, safe, and efficient and has strong scalability in data management, data analysis, and scalability. It reflects the innovation of the system and provides a good platform for the management, research, and analysis of clinical big data of schizophrenia.


2018 ◽  
Vol 232 ◽  
pp. 01010
Author(s):  
Jia Zhang

In order to improve the ability of library and information management in colleges and universities, and improve intelligent retrieval level of books, a design method of library information management system is proposed based on big data fusion. The phase space reconstruction technology is used to reconstruct the feature of library and information. The feature quantity of semantic concept set of library information is extracted, and the classification storage and information retrieval of library information is carried out by fuzzy clustering method. The adaptive training method is used for feature fusion, and big data fusion of library and information is realized in high dimensional feature space. The data processing center is set up under the Linux kernel environment, the application program of the university library information management system is developed under the Linux kernel, and the VXI bus technology is used to transmit and schedule the university library information management information and data. Realize the software development and design of the school library information management system. The test results show that the design of university library information management system with this method has good information storage and scheduling ability, and it improves the performance of library information retrieval. In the information recall rate and recall rate and other indicators performance has an advantage.


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