  Clustering is an unsupervised technique of Data Mining. It means grouping
similar objects together and separating the dissimilar ones. Each object in the
data set is assigned a class label in the clustering process using a distance
measure. This paper has captured the problems that are faced in real when
clustering algorithms are implemented .It also considers the most extensively
used tools which are readily available and support functions which ease the
programming. Once algorithms have been implemented, they also need to be tested
for its validity. There exist several validation indexes for testing the
performance and accuracy which have also been discussed here.
