BSc CSIT (TU) Science Data Warehousing and Data Mining (BSc CSIT, CSC410) Question Paper 2077
This is the official BSc CSIT (TU) (Science stream) Data Warehousing and Data Mining (BSc CSIT, CSC410) question paper for 2077, as set in the regular annual examination. It carries 60 full marks and a time allowance of 180 minutes, across 12 questions. On Kekkei you can attempt this Data Warehousing and Data Mining (BSc CSIT, CSC410) past paper online with a timer, get instant AI feedback and step-by-step solutions, and track the topics where you lose marks — completely free. Whether you are revising for your BSc CSIT (TU) Data Warehousing and Data Mining (BSc CSIT, CSC410) exam or solving previous years' question papers, this 2077 paper is a great way to practise under real exam conditions.
Section A: Long Answer Questions
Attempt any TWO questions.
Define data warehousing. Explain the data warehouse design process and the components of a data warehouse with a diagram.
What is cluster analysis? Explain the DBSCAN algorithm. Given a dataset with Eps = 2.5 and MinPts = 3, identify core points, border points, and outliers.
Explain the Apriori principle. Using the Apriori algorithm, generate frequent itemsets and association rules for a given transaction dataset.
Section B: Short Answer Questions
Attempt any EIGHT questions.
What is data transformation? List its techniques.
Differentiate between ROLAP and MOLAP.
Explain the bottom-up and top-down approaches of building a data warehouse.
What is a confusion matrix? How is it used to evaluate a classifier?
Explain the concept of data cube.
What is outlier analysis? Why is it important?
Define entropy and information gain.
Explain the partitioning method of clustering.
Write short notes on web mining.