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Book contain Concept Data Mining overview, Data Warehouse and OLAP Technology,Data Warehouse Architecture, Stepsfor the Design and Construction of Data Warehouses, A Three-Tier Data WarehouseArchitecture,OLAP,OLAP queries, metadata repository,Data Preprocessing – Data Integration and Transformation, Data Reduction,Data Mining Primitives:What Defines a Data Mining Task? Task-Relevant Data, The Kind of Knowledge to be Mined,KDD. What Is Cluster Analysis, Types of Data in Cluster Analysis,A Categorization of Major Clustering Methods, Classical Partitioning Methods: k-Meansand k-Medoids, Partitioning Methods in Large Databases: From k-Medoids to CLARANS, Hierarchical Methods, Agglomerative and Divisive Hierarchical Clustering,Density-BasedMethods, Wave Cluster: Clustering Using Wavelet Transformation, CLIQUE:Clustering High-Dimensional Space, Model-Based Clustering Methods, Statistical Approach,Neural Network Approach.