Analysis of Distributed Databases

Abstract

Data mining extract pattern/ knowledge from a large amount of database. In the applications that are based on the information sharing and additional challenges, when dealing with the data that containing sensitive or private information. There is no any common data mining techniques available that dealing with the private information without any leakage. There for the knowledge extracted from such data may disclose pattern with sensitive/ private information. This may put privacy on the individual/ group of parties. In the few last years, privacy preserving data mining has attracted the research interest and potential for wide area of applications. There are many techniques for privacy preservation like cryptography; anonymity and randomization etc. have been experimented for privacy preservation in data mining. In this paper we analyzed the different partitioning algorithm that is useful for partitioning the database in distributed environments.
Keywords: Database; Data Mining; Distributed Database; Partitioning Approach; Homogeneous Database; Heterogeneous Database.