An introduction:
Data Collection is the process of developing data from similar gatherings, which is a branch of data mining. Aggregation algorithm divides data sets into several clusters, as the similarities between the points within a certain grouping larger than the similarity between two points within the different two communities.

Target:
The vast amount of data to summarize a few of the groups or categories, in order to facilitate the process of analysis.

Methods Techniques:
(Data clustering) Used not only to organize and classify the data, but the data compression and build a model arrangement of data aggregation algorithms on a large scale. There are many algorithms used in the data collection process. The use of K-Means Clusterin algorithm so as to assemble several statements depending on their characteristics to K gathering, and the process of the assembly by reducing the distance between the data center and assembly (cluster centroid).

Software package:
that can use Excel or C ++ program or wWeka program.