4.6 Article

A Hybrid Infrastructure of Enterprise Architecture and Business Intelligence & Analytics for Knowledge Management in Education

期刊

IEEE ACCESS
卷 7, 期 -, 页码 38778-38788

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2906343

关键词

Big data; business intelligence; data warehouse; educational data mining; knowledge management

资金

  1. Universidad Tecnologica Equinoccial

向作者/读者索取更多资源

Advances in science and technology, the Internet of Things, and the proliferation of mobile apps are critical factors to the current increase in the amount, structure, and size of information that organizations have to store, process, and analyze. Traditional data storages present technical deficiencies when handling huge volumes of data and are not adequate for process modeling and business intelligence; to cope with these deficiencies, new methods and technologies have been developed under the umbrella of big data. However, there is still the need in higher education institutions (HEIs) of a technological tool that can be used for big data processing and knowledge management (KM). To overcome this issue, it is essential to develop an information infrastructure that allows the capturing of knowledge and facilitates experimentation by having cleaned and consistent data. Thus, this paper presents a hybrid information infrastructure for business intelligence and analytics (BI&A) and KM based on an educational data warehouse (EDW) and an enterprise architecture (EA) repository that allows the digitization of knowledge and empowers the visualization and the analysis of dissimilar organizational components as people, processes, and technology. The proposed infrastructure was created based on research and will serve to run different experiments to analyze educational data and academic processes and for the creation of explicit knowledge using different algorithms and methods of educational data mining, learning analytics, online analytical processing (OLAP), and EA analytics.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据