CS-703 (B) 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
4 papers, latest Dec 2025
- CS-703 (B) paper, Dec 2025
- CS-703 (B) paper, Jun 2025
- CS-703 (B) paper, Dec 2024
- CS-703 (B) paper, Nov 2023
Syllabus, notes and important questions for CS-703 (B)
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
- Multidimensional Data Model
- Pattern Warehousing
Unit 2 OLAP Systems 7 topics
- Basic concepts of OLAP
- OLAP queries
- Types of OLAP servers
- OLAP operations
- Data Warehouse Hardware Design
- Security
- Backup and Recovery
Unit 3 Introduction to Data & Data Mining 11 topics
- Data Types
- Data Quality
- Data Preprocessing
- Similarity Measures
- Summary Statistics
- Data Distributions
- Basic Data Mining Tasks
- Data Mining vs Knowledge Discovery in Databases
- Issues in Data Mining
- Fuzzy Sets
- Fuzzy Logic
Unit 4 Supervised Learning 6 topics
- Classification – Statistical‑based algorithms
- Classification – Distance‑based algorithms
- Classification – Decision‑tree‑based algorithms
- Classification – Neural‑network‑based algorithms
- Classification – Rule‑based algorithms
- Probabilistic Classifiers
Unit 5 Clustering & Association Rule Mining 7 topics
- Hierarchical Clustering Algorithms
- Partitional Clustering Algorithms
- Clustering large databases – BIRCH
- Clustering large databases – DBSCAN
- Clustering large databases – CURE
- Association Rules – Apriori algorithm
- Association Rules – FP‑growth algorithm
Exam insights
Counted from 4 past CS-703 (B) papers.
Marks asked per paper, by unit
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Unit 1 Data Warehousing: Introduction 33 marks
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Unit 2 OLAP Systems 19 marks
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Unit 3 Introduction to Data & Data Mining 28 marks
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Unit 4 Supervised Learning: Classification 10 marks
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Unit 5 Clustering & Association Rule mining 19 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 the different types of data warehouse / multidimensional schemas (star schema, snowflake schema, fact constellation schema) with suitable examples.
Asked 5 times: 2025, 2024, 2023
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Define OLAP and explain/compare the different types/categorization of OLAP servers/tools (MOLAP, ROLAP, HOLAP).
Asked 4 times: 2025, 2024, 2023
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Define data warehousing and explain the three-tier data warehouse architecture with a suitable diagram.
Asked 4 times: 2025, 2024, 2023, 2020