Research on the Big Data Collection Mechanism of University Economic Management
- DOI
- 10.2991/978-94-6463-030-5_90How to use a DOI?
- Keywords
- University; Economic Management Data; Collection Content; Collection Method; Collection Path
- Abstract
In order to explore the school’s economic management big data collection mechanism, build a school’s economic management big data integration platform to provide innovative ideas. This article forms a collection content system from the four aspects of service object, service process, operation support, and external contact. At the same time, it uses data dictionary table design method, data flow table design method, and correlation method to show the collection methods of university economic management big data. Strive to give full play to the value and role of the school’s economic management big data integration platform, expand the depth and breadth of data collection, and form a panoramic data view. It is of great significance to improve the efficiency of university service economic behavior, form data-driven agile decision-making, and promote the sustainable development of the school economy and the implementation of the national big data strategy.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Ying Zhang AU - Yongwei Li PY - 2022 DA - 2022/12/20 TI - Research on the Big Data Collection Mechanism of University Economic Management BT - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022) PB - Atlantis Press SP - 916 EP - 925 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-030-5_90 DO - 10.2991/978-94-6463-030-5_90 ID - Zhang2022 ER -