Cluster analysis is used to define the object without giving the class label. It analyzes all the data that is present in the Data Warehouse and compares the cluster with the cluster that is already running. It performs the task of assigning some set of objects into groups, also known as clusters. It is used to perform the data mining job using a technique like statistical data analysis. It includes all the information and knowledge around many fields such as Machine Learning, pattern recognition, image analysis, and bio-informatics. Cluster analysis performs the iterative process of knowledge discovery and includes trials and failures. It is used with the pre-processing and other parameters to achieve the properties that are desired to be used.
Purpose of cluster analysis:
Scalability
Ability to deal with different kinds of attributes
Discovery of clusters with attribute shape
High dimensionality
Ability to deal with noise
Interpretability
Learn more about Data Warehousing in this insightful Data Warehouse Tutorial!