CS-703 (B) · Data Mining and Warehousing/Official Syllabus
Data Mining and Warehousing (CS-703 (B)) - Official Syllabus
1
Unit 1
Data Warehousing: Introduction
- Introduction
- Delivery Process
- Data warehouse Architecture
- Data Preprocessing: Data cleaning
- Data Integration and transformation
- Data reduction
- Data warehouse Design: Datawarehouse schema
- Partitioning strategy
- Data warehouse Implementation
- Data Marts
- Meta Data
- Example of a Multidimensional Data model
- Introduction to Pattern Warehousing
2
Unit 2
OLAP Systems
- Basic concepts
- OLAP queries
- Types of OLAP servers
- OLAP operations etc.
- Data Warehouse Hardware and Operational Design: Security
- Backup And Recovery
3
Unit 3
Introduction to Data & Data Mining
- Data Types
- Quality of data
- Data Preprocessing
- Similarity measures
- Summary statistics
- Data distributions
- Basic data mining tasks
- Data Mining V/s knowledge discovery in databases.
- Issues in Data mining.
- Introduction to Fuzzy sets and fuzzy logic
4
Unit 4
Supervised Learning: Classification
- Statistical-based algorithms
- Distance-based algorithms
- Decision tree-based algorithms
- Neural network-based algorithms
- Rule-based algorithms
- Probabilistic Classifiers
5
Unit 5
Clustering & Association Rule mining
- Hierarchical algorithms
- Partitional algorithms
- Clustering large databases - BIRCH
- DBSCAN
- CURE algorithms.
- Association rules : Parallel and distributed algorithms such as Apriori
- FP growth algorithms
Reference Books
- Data Mining : Introductory and Advanced topics — Margaret H. Dunham
- Data Warehousing in the Real World — Anahory, Murray
- Introduction to Data Mining — Pang-Ning Tan, Steinbach, Kumar
- Data Mining : Concepts and Techniques — Jaiwei Han, Micheline Kamber
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