Data Warehousing and Mining — Winter 2023

Explain any three OLAP operations with suitable example.

Discuss Data Smoothing by Binning using suitable example.

EWxhpalat iins KDDatDa Mproinciensgs.? Why is it called Data Mining rather Knowledge Mining? Explain KDD process.

Explain the major issues in Data Mining.

Compare OLAP and OLTP systems.

What is an ‘Outlier’? How do Outliers impact the results of Mining? Explain any one method to detect Outliers.

Explain Linear and Non-linear Regression.

Define Euclidean Distance, Manhattan Distance & Minkowski Distance.

List and explain types of Concept Hierarchy.

List out the different schema of Data Warehouse and explain one of the Data Warehouse schemas in detail with suitable diagram.

Define Supervised Learning, Unsupervised Learning & Data Reduction.

Explain Five Number Summary with suitable database example.

What do you mean by Data Mart? What are the different types of Data Mart?

Explain about role of Principal Component of Analysis (PCA).

What is Data Transformation? Explain the different Data Transformation approaches for Transforming Data.

Define Sampling. Explain different type of Sampling Techniques with suitable example.

Define Bayes’ Theorem.

What is Data Cleaning? Describe the different methods of handling missing values during Data Cleaning.

Define Noise. Explain the different techniques to remove the Noise from Data.

Explain Information Gain and Gain Ratio.

Write a short note on Web Mining.

What is Decision Tree Induction? Write Basic Algorithm for inducing a Decision Tree from training tuples.

Explain Market Basket Analysis.

Write a short note on Text Mining.

Explain the steps of the Apriori algorithm for mining frequent item sets with candidate generation.