Big Data representation for grade analysis through Hadoop framework

Abstract

Big Data is a large dataset displaying the features of volume, velocity and variety in an OR relationship. Big Data as a large dataset is of no significance if it cannot be exposed to strategic analysis and utilization. There are many software and hardware solutions available in the technological landscape that enable capturing, storing and subsequently analysis of Big Data. Hadoop and its associated technological solution is one of them. Hadoop is the software framework for computing large amount of data. It is made up of four main modules. These modules are Hadoop Common, Hadoop Distributed File System (HDFS), Hadoop YARN, and Hadoop MapReduce. Hadoop MapReduce divides large problem into smaller sub problems under the control of JobTracker. This paper suggests a Big Data representation for grade analytics in an educational context. The study and the experiments can be implemented on R or AWS the cloud infrastructure provided by Amazon.