Data Warehousing and Data Mining for GTU ( VII-IT-2008 course )

By Manmohan Singh
Publisher: Technical Publications
ISBN: 9789333202282
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Introduction to Data Warehousing Why reporting and analyzing data, Raw data to valuable information - Lifecycle of data - What is data warehousing - The building blocks : Defining features - Data warehouses and data marts - Overview of the components - Metadata in the data warehouse - Need for data warehousing - Basic elements of data warehousing - Trends in data warehousing. Introduction to Data Mining Motivation for data mining - Data mining : On what kind of data ? - Definition and functionalities : What kind of patterns can be mined ? - Classification of DM systems - Integration of a data mining system with a database or a data warehouse - Issues in DM - KDD process. Data Preprocessing and Data Mining Primitived Why preprocess the data ? Data cleaning - Data integration and transformation - Data reduction - Discretization and concept hierarchy generation - Data mining primitives : What defines a data mining task ? Concept Description and Association Rule Mining What is concept description ? Data generalization and summarization - Based characterization - Attribute relevance - Class comparisons association rule mining : Market basket analysis - Basic concepts - Finding frequent item sets : Apriori algorithm - Generating rules - Improved Apriori algorithm - Incremental ARM - Associative classification - Rule mining. Classification and Clustering What is classification and prediction ? - Issues regarding classification and prediction : Classification methods : Decision tree, Bayesian classification, Rule based, CART, Neural network, CBR, Rough set approach, Fuzzy logic, Genetic algorithms - Prediction methods : Linear and non linear regression, Logistic regression - What is cluster analysis ? - Types of data in cluster analysis - A categorization of major clustering methods, Types of clustering algorithms. Advance Topics of Data Mining and its Applications Mining time - Series and sequence data - Mining text databases - Mining the World Wide Web - Data mining application.
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