AD-603 (A) RGPV B.Tech
Data Mining and Warehousing (DMW)
Previous year papers and the official syllabus are free to read, no account needed.
Previous Year Papers
3 papers, latest Jun 2025
Syllabus, notes and important questions for AD-603 (A)
Syllabus units
Topics as the official RGPV syllabus lists them.
Unit 1 Data Warehousing 13 topics
- Introduction
- Delivery Process
- Data warehouse Architecture
- Data cleaning
- Data Integration and transformation
- Data reduction
- Data warehouse schema
- Partitioning strategy
- Data warehouse Implementation
- Data Marts
- Meta Data
- Example of a Multidimensional Data model
- Introduction to Pattern Warehousing
Unit 2 OLAP Systems 7 topics
- Basic concepts
- OLAP queries
- Types of OLAP servers
- OLAP operations
- Data Warehouse Hardware and Operational Design
- Security
- Backup and Recovery
Unit 3 Introduction to Data & Data Mining 10 topics
- Data Types
- Quality of data
- Data Preprocessing
- Similarity measures
- Summary statistics
- Data distributions
- Basic data mining tasks
- Data Mining vs knowledge discovery in databases
- Issues in Data mining
- Introduction to Fuzzy sets and fuzzy logic
Unit 4 Supervised Learning: Classification 6 topics
- Statistical-based algorithms
- Distance-based algorithms
- Decision tree-based algorithms
- Neural network-based algorithms
- Rule-based algorithms
- Probabilistic Classifiers
Unit 5 Clustering & Association Rule Mining 7 topics
- Hierarchical algorithms
- Partitional algorithms
- Clustering large databases - BIRCH
- DBSCAN
- CURE algorithms
- Parallel and distributed association rule algorithms such as Apriori
- FP growth algorithms
Exam insights
Counted from 3 past AD-603 (A) papers.
Marks asked per paper, by unit
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Unit 1 Data Warehousing 19 marks
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Unit 2 OLAP Systems 21 marks
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Unit 3 Introduction to Data & Data Mining 26 marks
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Unit 4 Supervised Learning: Classification 21 marks
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Unit 5 Clustering & Association Rule mining 12 marks
Average marks of the questions from each unit in one paper. You answer only some of them, so the total is more than the paper’s maximum.
Asked again and again
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Explain typical OLAP operations on multidimensional data cubes with examples and diagrams.
Asked 4 times: 2025, 2024, 2023
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Explain the various phases of the knowledge discovery (KDD) process and data mining as a step within it, with a neat diagram.
Asked 3 times: 2025, 2024, 2023
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Explain the rule-based classifier/algorithm including structure, working, example, use of information gain, real-world applications, strengths, limitations and future evolution.
Asked 3 times: 2025, 2024