Designing a Data Cube for Student Drop-Out Study
Pranjal Kalita · SSRN Electronic Journal · 2011
A data cube is a multidimensional model which represents data in different aspects. The OnLine Analytical Processing (OLAP) operations like slicing, dicing, roll-up and drill-down help to view the data in the data cube from different perspectives. Analyzing the different combinations of dimensions of the cube can get some patterns. Data cube has many applications in real life problems, among which student drop-out in an educational institution is a significant one. The drop-out of students from educational institutes has always been a serious issue. This paper presents the design of a data cube to study the pattern of student drop-out in any educational institution. To analyze the past data of a drop-out student, the paper proposes a data cube, for which six different dimensions - year, sex, monthly family income, category, qualifying exam marks and course - have been considered. These dimensions are the attributes chosen from the student's admission form. The 'number of students admitted' and 'number of student drop-outs' are two measures which are numeric in nature. Once the pattern of the drop-out students is obtained from the cube, it will be helpful to the concerned organization for decision support during student admissions.