Construction of digital case resources for the cultivation of big data professionals
With the rapid advancement of big data industry, professional education pertaining to big data has garnered substantial global recognition. However, the gap between practical teaching methodologies and real-world application scenarios represents a significant hurdle in fostering skilled big data pro...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
China InfoCom Media Group
2025-01-01
|
| Series: | 大数据 |
| Subjects: | |
| Online Access: | http://www.j-bigdataresearch.com.cn/zh/article/doi/10.11959/j.issn.2096-0271.2025007/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | With the rapid advancement of big data industry, professional education pertaining to big data has garnered substantial global recognition. However, the gap between practical teaching methodologies and real-world application scenarios represents a significant hurdle in fostering skilled big data professionals. To address this challenge, this paper proposes the construction of a comprehensive digital case library tailored for core courses in big data. This library, alongside innovative integration strategies, aims to bridge the gap between theory and practice. This paper outlines a structured approach to establish a systematic and serialized data resource case library, adopting a dynamic hierarchical design that comprehensively illustrates the entire big data processing workflow while enabling dynamic expansion. The objective is to contribute to the enhancement of big data curricula and practical teaching, ultimately empowering the practical abilities cultivation of big data professionals. Taking the digital case study of "high-risk population cardiovascular and cerebrovascular disease" as an example, this paper delves into the curriculum model and implementation strategies that seamlessly integrate case resources with theoretical teachings. Through collaboration with a national data center, we achieve a close alignment between practical teaching and real-world application scenarios. The construction of this caselibrary resource will bolster the theoretical acumen and practical proficiencies of big data professionals. |
|---|---|
| ISSN: | 2096-0271 |