A proposed architecture of big educational data using hadoop at the University of Kufa - Ahmed Yaseen Mjhool; Ahmed Hazim Alhilali; Salam Al-augby (Institute of Advanced Engineering and Science, 2019)
Nowadays, educational data have been increased rapidly because of the online services provided for both students and staff. University of Kufa (UoK) generates a massive amount of data annually due to the use of e-learning web-based systems, network servers, Windows applications, and Students Information System (SIS). This data is wasted as traditional management software are not capable to analysis it. As a result, the Big Educational Data concept rises to help education sectors by providing new e-learning methods, allowing to meet individual demands and reach the learners' goals, and supporting the students and teacher’s interaction. This paper focuses on designing Big Data analysis architecture, based on the Hadoop in the UoK and the same case for other Iraqi universities. The impact of this work, help the students learn, emphasizing the need of academic researchers and data science specialist for learning and practicing Big Data analytics and support the analysis of the e-learning management system and set the first step toward developing data repository and data policy in UoK.