The Mining of the education data is emerging trend in the learning analytics as it is time consuming to analyses the data and to identify the hidden information automatically. In this paper, detailed investigation about the educational data mining technique is carried out. The Application of the data mining includes storing and retrieval of the student data in the large repositories such as mark sheet, attendance sheet and student profile etc. The importance analysis is carried out on the retrieval of the large data using machine learning algorithm in the data mining. Along the retrieval of the data, nowadays deep focus is made on predicting and recommendation models which provide more effectiveness to the educational applications in terms of suggestions and extracting the correlation among the students. However, handling of large data from repositories leads to performance bottleneck, hence it is resolved by employing Map Reduce Paradigm from big data analytics. Through extensive study, classification and clustering provides more value for the data management, hence semantic and opinion mining is presented as the future research solution.