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PYQ Analysis

MCS-221 · 9 papers · Dec 2021, Jun 2022, Dec 2022, Jun 2023, Dec 2023, Jun 2024, Dec 2024, Dec 2025

Block Weightage

Block 1 — Data Warehouse Fundamentals and Architecture

~26 marks/paper · 9/9 papers · 3 units

28%

Block 2 — ETL, OLAP and Trends

~22 marks/paper · 9/9 papers · 3 units

25%

Block 3 — Data Mining Fundamentals and Frequent Patterns

~21 marks/paper · 9/9 papers · 3 units

23%

Block 4 — Classification, Clustering and Web Mining

~21 marks/paper · 9/9 papers · 3 units

23%

Unit Breakdown

Unit 1 — Fundamentals of Data Warehouse

Must

~10 marks · 100% frequency

Data Warehouse Definition & CharacteristicsTypes of Data Warehouses (EDW, ODS)Data Warehouse vs Data MiningData Lake vs Data WarehouseData Lake Architecture & StagesCloud Data WarehousingData GranularityMetadata and Data Warehousing

Unit 2 — Data Warehouse Architecture

Must

~10 marks · 90% frequency

Single-Tier ArchitectureThree-Tier ArchitectureReal-Time Data Warehouse ArchitectureHadoop Data Warehouse ArchitectureTop-Down Approach (Bill Inmon)Bottom-Up Approach (Kimball)Data Warehouse Best Practices & ChallengesData Marts (Dependent & Independent)Operational Data Store (ODS)

Unit 3 — Dimensional Modeling

Must

~10 marks · 95% frequency

Facts, Fact Table, Dimensions, Dimensional TableStar SchemaSnowflake SchemaFact Constellation SchemaAggregate Fact Tables & Derived Dimension TablesComplex Data Modeling

Unit 4 — Extract, Transform and Loading

Must

~10 marks · 100% frequency

ETL: Extract, Transform, LoadLayered Implementation of ETLETL Performance ImprovementELT vs ETLData Warehouse Automation

Unit 5 — Introduction to OLAP

Must

~10 marks · 90% frequency

OLAP Definition & ApplicationsOLAP Operations: Roll-up, Drill-down, Slice, DiceMOLAP ArchitectureROLAP ArchitectureHOLAP ArchitectureMulticube vs HypercubeOLTP vs OLAP

Unit 6 — Trends in Data Warehouse

~6 marks · 70% frequency

Cloud Data WarehousingData Warehouse Automation

Unit 7 — Data Mining: An Introduction

~6 marks · 75% frequency

Data Mining Definition & ApplicationsData Mining Tasks & TechniquesData Mining Life CycleData Mining Issues

Unit 8 — Data Preprocessing

Must

~10 marks · 100% frequency

Data Cleaning (Missing Values, Noisy Data)Binning Method for Noisy DataData Integration IssuesData Reduction (Dimensionality Reduction)Feature Selection & Feature ExtractionData TransformationLDA & PCA Feature Extraction

Unit 9 — Mining Frequent Patterns

Must

~10 marks · 95% frequency

Association Rule MiningSupport, Confidence, LiftApriori AlgorithmMarket Basket AnalysisFrequent Pattern Mining ClassificationsMining Multilevel Association Rules

Unit 10 — Classification

Must

~10 marks · 100% frequency

Classification: Descriptive & Predictive ModelingDecision Tree (Construction & Representation)Rule-Based ClassificationK-Nearest Neighbour (KNN) AlgorithmNaive Bayes ClassifierResampling Methods (K-fold, LOO, etc.)Outlier DetectionRegression Analysis

Unit 11 — Clustering

Must

~10 marks · 95% frequency

Cluster Analysis Definition & ApplicationsK-Means AlgorithmK-Medoids AlgorithmPartitioning MethodDensity-Based Method (DBSCAN)Hierarchical Method (Agglomerative)Constraint-Based Method

Unit 12 — Text and Web Mining

Must

~8 marks · 85% frequency

Text Mining Definition & ApplicationsText Preprocessing (Tokenization, Stemming)Vector Space Model, TF-IDFBag-of-Words (BoW)Text Categorization & SummarizationDimensionality Reduction for TextWeb Mining: Content, Structure, UsagePageRank, HITS, Page Layout AnalysisMining Multimedia Data on the Web

Most Repeated Model Questions

1

Explain the ETL Process of a Data Warehouse with a block diagram. How is it different from ELT?

🔥 8x asked📚 Extract, Transform and Loading⭐ 10 marks📅 Dec 2025
2

Write and explain the Apriori Algorithm used to identify frequently occurring elements and meaningful associations in a dataset.

🔥 5x asked📚 Mining Frequent Patterns⭐ 10 marks📅 Dec 2024