Mining Functional Dependency in Relational Databases using FUN and Dep-Miner: A Comparative Study

Abstract

Database is a collection of tables of data items, if the database is organized according to relational model it is called relational database. In a relational database, a logical and efficient design is just as critical. A poorly designed database may provide erroneous information, or may even fail to work properly may be difficult to use. Most of these problems are the result of two bad design features called redundant data and anomalies. Database normalization is the process of designing a database satisfying a set of integrity constraints, efficiently and in order to avoid inconsistencies when manipulating the database. Most of the research work has been devoted to functional dependencies. There are several algorithms have been developed in the past year like TANE, FD_Mine FD_Discover, Dep-Miner, FUN, FD Analysis using Rough sets, FD discovery by Bayes Net. In This paper we present a comparative study over Dep-Miner and FUN. We compare the working process of Dep-Miner and FUN using a simple example.