Description

ABSTRACT 

Handling large and voluminous data is a tough task even for experts in SQL. The problem is even more difficult

for a user who lacks SQL expertise or familiarity with the database schema. This project aims at helping this class

of users by giving them suggestions of SQL queries that they might use. These SQL suggestions are selected by

profiling the users past behavior and comparing them with other users. The queries are fragmented and ranked

according to relevance and the relevant queries are retrieved using ‘User’s Querying Behavior’.