In today's industry, databases are extremely large in size and within these masses of data lies hidden information of strategic importance. The task of finding patterns and relationships in these huge databases is accomplished by the data mining concept. Our Dataset belongs to student details for finding out the retention of students in the Texas A&M University , Commerce.

The database consists of the details of the freshman students of A&M, Commerce. The details include their Ethnicity, Residence Area, Tuition Status, Gender, Credit Hours enrolled etc.

We implemented Intelligent User Interface, Data Mining Using Apriori, Conditional Probability and Attribute Oriented Induction on “Student Details” Database. We were able to determine hidden patterns between various attributes which is usually not possible using traditional methods of data analysis.

This website is deployed for the development and demonstration of data warehousing and data mining techniques and it application on large amounts of data.

This is a project work done as part of the study of Intelligent Databases(CSCI - 527).