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.
For Answers – https://Madhav.topsecret.link/lchjt
src:
