Online Analytical Processing Technique in Personalizing Student Academic Pattern Behavior for

Azwa, Abdul Aziz and Wan Mohd Rizhan, Wan Idris Online Analytical Processing Technique in Personalizing Student Academic Pattern Behavior for. In: The International Conference Digital Enterprise & Information System (DEIS 2011), July 20-22 2011, London Metropolitan Business School.

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Business Intelligence (BI) refers to skills, processes, technologies, applications and practices used to support decision making. BI technologies provide historical, current, and predictive views of business operations which are normally used to analyze business data. Online Analytical Processing (OLAP) is one of the common BI approaches in quickly answering multi-dimensional analytical queries for analytical purpose. In this paper, we have proposed OLAP technique to be implemented in Academic area. Through this technique, UniSZA students’ academic pattern behaviors can be analyzed. A set of data from students’ examination results in relational DB is extracted into multi-dimensional model to support OLAP query processing. The results are grouped into several subject areas. Then, the analysis to recognize students’ academic pattern behaviors is conducted. From the analysis, the groups of students who have the excellent skills or vice versa can be identified. It also optimizes the time dimension to perform current and historical data analysis. The weaknesses and strengths of the student can also be obtained. Finally, students’ future potential areas can be predicted for the next level of educations.

Item Type: Conference or Workshop Item (Paper)
Keywords: Data Warehouse, BI, OLAP, Multidimensional Model
Subjects: A General Works > AI Indexes (General)
L Education > L Education (General)
Faculty / Institute: Faculty of Informatics & Computing
Depositing User: Mr. Azwa bin Aziz
Date Deposited: 27 Oct 2014 07:22
Last Modified: 27 Oct 2014 07:22

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