10IS74 Data Warehousing and Data Mining syllabus for IS


Part A
Unit-1 Data Warehousing 6 hours

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

Unit-2 Online Analytical Processing (OLAP) 6 hours

Introduction, Characteristics ofOLAP systems, Multidimensional view and Data cube, Data CubeImplementations, Data Cube operations, Implementation of OLAP andoverview 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 MiningApplications

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

Frequent ItemsetGeneration, 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 ofclassification 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 ofData and Computing Distance, Types of Cluster Analysis Methods,Partitional Methods, Hierarchical Methods, Density Based Methods, Qualityand Validity of Cluster Analysis

Unit-8 Web Mining 6 hours

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

Last Updated: Tuesday, January 24, 2023