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IT-603 (B) · Data Mining/Official Syllabus

Data Mining (IT-603 (B)) - Official Syllabus

1
Unit 1

Data Warehousing

  • Need for data warehousing
  • Basic elements of data warehousing
  • Data Mart
  • Data Warehouse Architecture
  • extract and load Process
  • Clean and Transform data
  • Star, Snowflake and Galaxy Schemas for Multidimensional databases
  • Fact and dimension data
  • Partitioning Strategy-Horizontal and Vertical Partitioning
  • Data Warehouse and OLAP technology
  • Multidimensional data models and different OLAP Operations
  • OLAP Server: ROLAP, MOLAP
  • Data Warehouse implementation
  • Efficient Computation of Data Cubes
  • Processing of OLAP queries
  • Indexing data
2
Unit 2

Data Mining

  • Data Preprocessing
  • Data Integration and Transformation
  • Data Reduction
  • Discretizaion and Concept Hierarchy Generation
  • Basics of data mining
  • Data mining techniques
  • KDP (Knowledge Discovery Process)
  • Application and Challenges of Data Mining
3
Unit 3

Mining Association Rules in Large Databases

  • Association Rule Mining
  • Single-Dimensional Boolean Association Rules
  • Multi-Level Association Rule
  • Apriori Algorithm
  • Fp-Growth Algorithm
  • Time series mining association rules
  • latest trends in association rules mining
4
Unit 4

Classification and Clustering

  • Distance Measures
  • Types of Clustering Algorithms
  • K-Means Algorithm
  • Decision Tree
  • Bayesian Classification
  • Other Classification Methods
  • Prediction
  • Classifier Accuracy
  • Categorization of methods
  • Outlier Analysis
5
Unit 5

Introduction of Web Mining and its types

  • Introduction of Web Mining and its types
  • Spatial Mining
  • Temporal Mining
  • Text Mining
  • Security Issue
  • Privacy Issue
  • Ethical Issue

Reference Books

  • Data Mining Technique
  • Data Mining Concepts & Techniques
  • Data Warehousing Fundamentals
  • Data Mining Introductory & Advanced Topics
  • The Data Warehouse Lifecycle Tool Kit
  • The Decision Support & Data Warehouse Systems
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