Predicting University Dropout through Data Analysis

University dropout is an issue which influences all colleges around the globe, such as, decreased enrolment, diminished income for the college, and monetary misfortunes for the State which supports the investigations, and establishes a social issue for undergraduate studies, their families, and society at large. Henceforth the significance of anticipating the percentage of dropout, in other words, recognize drop out of the undergraduate studies ahead of time, helps us to develop prior plans and solutions/alternative procedures to handle this issue. Here University data is isolated by utilizing Hadoop with HDFS, map-reduce, sqoop, hive and R. By employing these for the University data, find the better performer, average and poor performers, as well as their sports excellence, other skills, their participation interests, other activities involvement and other factors to isolate the poor performers and the students who are likely in the thought process of dropping out. By filtering such students priorly, helps us to suggest their department heads and by which proper attention may be given to these students and retain them without dropping out. It helps us to concentrate and practice extra care for these low performers and push them for scoring better grades. Various sorts of learning framework can be utilized to limit the odds of being a dropout. This will lessen the dropout paces of the college undergraduate studies.