R07 4-1 DATA WAREHOUSING AND DATA MINING Syllabus

UNIT - I

Introduction : Fundamentals of data mining, Data Mining Functionalities, Classification of Data Mining 

 

systems, Major issues in Data Mining.

Data Preprocessing : Needs Preprocessing the Data, Data Cleaning, Data Integration and 

 

Transformation, Data Reduction, Discretization and Concept Hierarchy Generation.

UNIT – II

Data Warehouse and OLAP Technology for Data Mining Data Warehouse, Multidimensional Data Model, 

 

Data Warehouse Architecture, Data Warehouse 

 

Implementation,Further Development of Data Cube Technology, From Data Warehousing to Data Mining.

UNIT - III

Data Mining Primitives, Languages, and System Architectures : Data Mining Primitives, Data Mining 

 

Query Languages, Designing Graphical User Interfaces Based on a Data Mining Query Language 

 

Architectures of Data Mining Systems.

UNIT - IV

Concepts Description : Characterization and Comparison : Data Generalization and Summarization- 

 

Based Characterization, Analytical Characterization: Analysis of Attribute Relevance, Mining Class

Comparisons: Discriminating between Different Classes, Mining Descriptive Statistical Measures in Large 

 

Databases.

UNIT - V

Mining Association Rules in Large Databases : Association Rule Mining, Mining Single-Dimensional 

 

Boolean Association Rules from Transactional Databases, Mining Multilevel Association Rules from 

 

Transaction Databases, Mining Multidimensional Association Rules from Relational Databases and Data 

 

Warehouses, From Association Mining to Correlation Analysis, Constraint-Based Association Mining.

UNIT - VI

Classification and Prediction : Issues Regarding Classification and Prediction, Classification by 

 

Decision Tree Induction, Bayesian Classification, Classification by Backpropagation, Classification Based

on Concepts from Association Rule Mining, Other Classification Methods, Prediction, Classifier Accuracy.

UNIT - VII

Cluster Analysis Introduction : Types of Data in Cluster Analysis, A Categorization of Major Clustering 

 

Methods, Partitioning Methods, Density-Based Methods, Grid-Based Methods, Model-Based Clustering 

 

Methods, Outlier Analysis.

UNIT - VIII

Mining Complex Types of Data : Multimensional Analysis and Descriptive Mining of Complex, Data 

 

Objects, Mining Spatial Databases, Mining Multimedia Databases, Mining Time-Series and Sequence 

 

Data, Mining Text Databases, Mining the World Wide Web.

TEXT BOOKS :

1. Data Mining – Concepts and Techniques - JIAWEI HAN & MICHELINE KAMBER Harcourt India.

REFERENCES :

1. Data Mining Introductory and advanced topics –MARGARET H DUNHAM, PEARSON EDUCATION

2. Data Mining Techniques – ARUN K PUJARI, University Press.

3. Data Warehousing in the Real World – SAM ANAHORY & DENNIS MURRAY. Pearson Edn Asia.

4 Data Warehousing Fundamentals – PAULRAJ PONNAIAH WILEY STUDENT EDITION.

5. The Data Warehouse Life cycle Tool kit – RALPH KIMBALL WILEY STUDENT EDITION.