Proceedings of the 3rd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2019)

Study on Big Data Mining of Universities by the Fully Integrated Campus Datacenter Platform

Authors
Liwen Zhu, Qingpeng Nie
Corresponding Author
Liwen Zhu
Available Online July 2019.
DOI
10.2991/iccia-19.2019.84How to use a DOI?
Keywords
big data, shared data center, data cleaning and integration, information criteria, comprehensive college situation analysis.
Abstract

Mining big data of university and providing better services for users in university has become a key problem in data services phase of university informatization. Taking Rizhao Polytechnic as an example, this paper analyzes and studies this problem. A solution for the fully integrated campus datacenter platform is proposed, and its objectives and contents are also illustrated. The system framework of the integrated campus datacenter platform and its key technologies are detailed and discussed. Finally, the effects of this platform in the future are evaluated and summarized.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2019)
Series
Advances in Computer Science Research
Publication Date
July 2019
ISBN
10.2991/iccia-19.2019.84
ISSN
2352-538X
DOI
10.2991/iccia-19.2019.84How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Liwen Zhu
AU  - Qingpeng Nie
PY  - 2019/07
DA  - 2019/07
TI  - Study on Big Data Mining of Universities by the Fully Integrated Campus Datacenter Platform
BT  - Proceedings of the 3rd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2019)
PB  - Atlantis Press
SP  - 538
EP  - 541
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-19.2019.84
DO  - 10.2991/iccia-19.2019.84
ID  - Zhu2019/07
ER  -