Analyze and Predicting the Student Academic Performance Using Data Mining Tools

In order to get reliable students' data, there are various methods being followed at present in the educational field. One among them is Data Mining Technique. The current situation of Data mining techniques is popularly practiced in many institutions to locate the hidden data of the student. KDD (Knowledge Discovery in Databases) is a method to identify the functional information from huge data. This technique is largely practiced by various institutions to find various patterns of stored data. It can also be found and extract the information. This type of method can largely believed, explain different problems happened in various institutions like education, economic, business, statics, medicine and, sport. The current work intention is to move towards the student achievement in secondary education applying BI/DM techniques. At present, the student's grades, demography, social and school-related information i.e. real-world data, is gathered through reports and questionnaire given by school reports. For this purpose, the two core groups were taken under Binary/ five level categorization and deterioration tasks. The present paper focuses on scheming various methods that will useful to the teachers and administrators of the institution to locate the weak student and develop their cognitive levels and atmosphere in which the student learns. It can also be observed in the paper that the dissimilar categorization methods based on the characteristics are used, to individual group or class and examine them from the existing data to classify the learner based on their presentation in academics. The ultimate objective of this paper is to find the failure of the students to avoid them from tumbling out and develop their scholastic performance.