Abstract
With the adoption of cloud services for hosting knowledge delivery system in educational domain, there is a surplus quantity of education data being generated every day by current learning management system. Such data are associated with certain typical complexities that impose significant challenges for existing database management and analytics. Review of existing approaches towards educational data highlights that they do not offer full-fledged solution towards analytics and still there is an open-end problem. Therefore, the proposed system introduces a comprehensive framework which offers integrated operation of transformation, data quality, and predictive analytics. The emphasis is more towards achieving distributed analytical operation towards educational data in cloud. Implemented using analytical research methodology, the proposed system shows better analytical performance with respect to frequently used educational data analytical approaches.
Highlights
There has been significantly increase in adoption of technique in the area of education system in recent time
If the cloud-based educational services are running from different geographical regions, than there will be different origination point of such educational big data
After reviewing the existing approaches of analytical operation associated with educational domain, it has been observed that that present schemes have certain loopholes viz
Summary
Abstract—With the adoption of cloud services for hosting knowledge delivery system in educational domain, there is a surplus quantity of education data being generated every day by current learning management system. Such data are associated with certain typical complexities that impose significant challenges for existing database management and analytics. Implemented using analytical research methodology, the proposed system shows better analytical performance with respect to frequently used educational data analytical approaches
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