Abstract
With the ongoing integration of industrialization and informatization, enterprise information infrastructure has been steadily advancing, leading to a substantial surge in data volume generated within organizations. Military enterprises, in particular, face unique challenges such as distributed data sources, data confidentiality concerns, and limited data sharing capabilities. The traditional approach of manually transferring data using physical media yields low transmission efficiency and requires significant human resources. Furthermore, the lack of comprehensive planning and standardized frameworks during the initial stages of enterprise information system development has resulted in data silos throughout the organization. Consequently, the seamless integration of data links and efficient data management has emerged as a critical priority for enterprises. This research paper presents a comprehensive methodology for data exchange and management in the military industry sector. It encompasses key aspects such as establishing data links, designing top-level architectural plans, constructing and implementing robust data models, implementing effective data warehouse management, and ultimately achieving a unified and centralized data display process. Through the implementation of this methodology, the aim is to facilitate efficient data flow, provide users with clear visualizations of data processing outcomes, enable streamlined data management, and enhance the value of data assets within the enterprise.
P. Wu and X. Wang—Contributed equally to the paper as co-first authors.
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References
Wang, S., Wang, H.: Architecture big data: challenges. Curr. Situation Prospects 34(10), 1741–1752 (2011)
McKendrick, J.: Data-to-value: designing aiviodern enterprise data architecture that delivers more %T for the business. Database Trends Appl. 36(6) (2022)
Yulin, Y., Xianmin, Z.: A reliable ETL strategy and architecture design for data warehouse. Journal 10, 172–174+229 (2005)
Chen, Y., et al.: Chinese intracranial hemorrhage imaging database: constructing a structured multimodal intracranial hemorrhage data warehouse. Chin. Med. J. 136(13), 1632–1634 (2022)
Xueqi, C., Xiaolong, J.: Overview of big data systems and analysis technologies. Journal 25(09), 1889–1908 (2014)
Ma, R., Sun, E.D., Zou, J.: A spectral method for assessing and combining multiple data visualizations. Nat. commun. 14(1) (2023)
Yanchen, X.: Data Communication and Computer Networks. 2nd edn. People’s Post and Telecommunications Publishing House Co. Ltd. (2015)
Daniška, D., Vrban, B., Nečas, V.: Development of database structures and data exchange principles for nuclear decommissioning planning. Radiat. Prot. Dosim. 198(9–11), 740–746 (2022)
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Wu, P., Wang, X., Zhang, X., Gao, Z. (2023). A Method for Data Exchange and Management in the Military Industry Field. In: Yang, X., et al. Advanced Data Mining and Applications. ADMA 2023. Lecture Notes in Computer Science(), vol 14179. Springer, Cham. https://doi.org/10.1007/978-3-031-46674-8_47
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DOI: https://doi.org/10.1007/978-3-031-46674-8_47
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