10CS755 Data Warehousing and Data Mining syllabus for CS


Part A
Unit-1 Data Warehousing 6 hours

Introduction, Operational Data Stores (ODS), Extraction Transformation Loading (ETL), Data Warehouses. Design Issues, Guidelines for Data Warehouse Implementation, Data Warehouse Metadata

Unit-2 Online Analytical Processing (OLAP) 6 hours

Introduction, Characteristics of OLAP systems, Multidimensional view and Data cube, Data Cube Implementations, Data Cube operations, Implementation of OLAP and overview on OLAP Softwares.

Unit-3 Data Mining 6 hours

Introduction, Challenges, Data Mining Tasks, Types of Data,Data Preprocessing, Measures of Similarity and Dissimilarity, Data Mining Applications

Unit-4 Association Analysis: Basic Concepts and Algorithms 8 hours

Frequent Itemset Generation, Rule Generation, Compact Representation of Frequent Itemsets, Alternative methods for generating Frequent Itemsets, FP Growth Algorithm, Evaluation of Association Patterns

Part B
Unit-5 Classification -1 6 hours

Basics, General approach to solve classification problem, Decision Trees, Rule Based Classifiers, Nearest Neighbor Classifiers.

Unit-6 Classification - 2 6 hours

Bayesian Classifiers, Estimating Predictive accuracy of classification methods, Improving accuracy of clarification methods, Evaluation criteria for classification methods, Multiclass Problem.

Unit-7 Clustering Techniques 8 hours

Overview, Features of cluster analysis, Types of Data and Computing Distance, Types of Cluster Analysis Methods, Partitional Methods, Hierarchical Methods, Density Based Methods, Quality and Validity of Cluster Analysis

Unit-8 Web Mining 6 hours

Introduction, Web content mining, Text Mining, Unstructured Text, Text clustering, Mining Spatial and Temporal Databases.

Last Updated: Tuesday, January 24, 2023