Data Warehousing and Data Mining
⏰ How much time do you have?
Questions below update with thisWe'll show only the topics you can realistically cover.
Do din hai — ye actually kafi hai agar seriously padho 💪
2 din hai — ye actually kafi hai agar seriously padho. Schema diagrams bana bana ke practice karo. Distraction band karo.
📊 Topic Weightage by Block
9 papers · 2021–2025📝 Question Bank
2 Days plan · 18 questions
⭐ Must Practice First
14Data Lake Architecture & Stages
Real-Time Data Warehouse Architecture
Data Mart (Types & Design)
Star Schema Dimensional Modeling
Snowflake Schema
ETL: Extract, Transform and Load
OLAP Data Cube Operations
Noisy Data and Binning Method
Apriori Algorithm
Association Rule Mining
Decision Tree (Construction & Representation)
K-Nearest Neighbour (KNN) Algorithm
K-Means Clustering Algorithm
Text Mining Techniques
Good to Prepare
4Data Preprocessing Stages
Web Mining (Content, Structure, Usage)
Clustering Methods (Partitioning, Density, Hierarchical)
Fact Constellation Schema
✅ Pass Strategy (40+)
Q1 is compulsory (4 parts × 10 marks = 40 marks). Focus first on the 4 most repeated Q1 topics: ETL, Noisy Data/Binning, Star/Snowflake Schema, and KNN/Decision Tree. Then pick 3 optional questions from the easiest topics: Apriori, Clustering (K-Means), Data Mart. Total = ~45 marks.
⭐ Distinction Strategy (72+)
Master all Q1 topics across 9 papers (ETL, Noisy Data, Schema diagrams, KNN, Apriori). Add: OLAP operations, Clustering methods, Text/Web Mining, Data Lake, Real-Time DW Architecture. 20 priority answers memorised = 70+ marks guaranteed.