This Questions are contributed by Private Academy Engineering
MODULE 1 – DATA WAREHOUSING FUNDAMENTALS
- Compare OLTP and OLAP.
 - What Are the Basic Building Blocks of a Data Warehouse?
 - Difference Between Star Schema and Snowflake Schema.
 
MODULE 2 – INTRODUCTION TO DATA MINING, DATA EXPLORATION & DATA PRE-PROCESSING
- Explain Issues of Data Mining.
 - Explain Data Pre-Processing.
 - Explain Different Types of Attributes.
 - Discuss Data Visualization Techniques.
 - Describe the Steps Involved in Data Mining.
 
MODULE 3 – CLASSIFICATION
- What Are the Various Methods for Estimating a Classifier’s Accuracy?
 - Explain Decision Tree-Based Classification Approach with Example.
 - What Are the Various Issues Regarding Classification and Prediction?
 
MODULE 4 – CLUSTERING
- Explain K-Means and K-Medoids Algorithm.
 - Difference Between Agglomerative and Divisive Clustering Methods.
 
MODULE 5 – MINING FREQUENT PATTERNS AND ASSOCIATION
- Explain Multilevel and Multidimensional Association Rule Mining in Detail.
 - Explain Market Basket Analysis with an Example.
 - Explain Steps of the Apriori Algorithm.
 
MODULE 6 – WEB MINING
- What Is Web Mining?
 - Explain Page Rank Technique in Detail.
 - Explain Web Structure Mining and Web Usage Mining.
 - Explain CLARANS Extension in Web Mining.
 - Explain Structure of a Web Log with an Example.
 
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