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Data Warehouse and Mining ( Solved Syllabus )

UNIT 1

Need for strategic information, difference between operational and
Informational data stores
Data warehouse definition, characteristics, Data warehouse role and
structure, OLAP Operations, Data mart, Different between data mart and
data warehouse, Approaches to build a data warehouse, Building a data
warehouse, Metadata & its types

UNIT 2

ta Pre-processing: Need, Data Summarization, Methods.
Denormalization, Multidimensional data model, Schemas for multidimensional data (Star schema, Snowflake Schema, Fact Constellation
Schema, Difference between different schemas.
Data warehouse architecture, OLAP servers, Indexing OLAP Data,
OLAP query processing, Data cube computation

UNIT 3

Data Mining: Definition, Data Mining process, Data mining
methodology, Data mining tasks, Mining various Data types & issues.
Attribute-Oriented Induction, Association rule mining, Frequent itemset
mining, The Apriori Algorithm, Mining multilevel association
rules.

UNIT 4

Overview of classification, Classification process, Decision tree,
Decision Tree Induction, Attribute Selection Measures. Overview of
classifier’s accuracy, Evaluating classifier’s accuracy, Techniques for
accuracy estimation, Increasing the accuracy of classifier. [CO4]
Introduction to Clustering, Types of clusters, Clustering methods, Data
visualization & various data visualization tools