  Large, data centric applications are characterized by its different
attributes. In modern day, a huge majority of the large data centric
applications are based on relational model. The databases are collection of
tables and every table consists of numbers of attributes. The data is accessed
typically through SQL queries. The queries that are being executed could be
analyzed for different types of optimizations. Analysis based on different
attributes used in a set of query would guide the database administrators to
enhance the speed of query execution. A better model in this context would help
in predicting the nature of upcoming query set. An effective prediction model
would guide in different applications of database, data warehouse, data mining
etc. In this paper, a numeric scale has been proposed to enumerate the strength
of associations between independent data attributes. The proposed scale is
built based on some probabilistic analysis of the usage of the attributes in
different queries. Thus this methodology aims to predict future usage of
attributes based on the current usage.
