A Survey on Data Mining Techniques in Distributed Databases
Main Article Content
Abstract
Data Mining is the process of discovering interesting patterns & Knowledge from large amounts of data. The
data can be gathered from different sources like Databases, Data Warehouses, the web, other information Repositories. In
client/server environment Distributed Databases play an important role for information processing and it is easy to foresee
that their importance will rapidly grow. Because of increased growth of data sharing, distributed databases are developed. In
Distributed Databases it is difficult to maintain large amounts of data in centralized databases without duplication & to
maintain secured data. In distributed databases, copy of data is stored in different locations, where memory wastage is
heavy. In many situations data is gathered from many places for analysis, where a privacy problem occurs. So, to avoid all
this Data Mining give Distributed Data Mining(DDM) to identify correct & perfect information. In this paper I am going to
concentrate on how to give security to Distributed Databases by using Data Mining Techniques like Privacy Preserving Data
Mining(PPDM),Association Rule for frequent patterns, Horizontal & Vertical partitions etc.
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