BSc CSIT (TU) Science Data Warehousing and Data Mining (BSc CSIT, CSC410) Question Paper 2079
This is the official BSc CSIT (TU) (Science stream) Data Warehousing and Data Mining (BSc CSIT, CSC410) question paper for 2079, 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 2079 paper is a great way to practise under real exam conditions.
Section A: Long Answer Questions
Attempt any TWO questions.
What is a data warehouse? Explain the three-tier architecture of a data warehouse in detail with a neat diagram.
Explain the K-means algorithm. Cluster the given set of points into two clusters and show all iterations until convergence.
What is classification? Explain the K-Nearest Neighbour (KNN) algorithm and classify a new instance for a given dataset.
Section B: Short Answer Questions
Attempt any EIGHT questions.
Differentiate between operational database and data warehouse.
Explain the OLAP operations with examples.
What is market basket analysis?
Explain the candidate generation step in Apriori.
What is overfitting in classification? How can it be avoided?
Explain the silhouette coefficient for cluster evaluation.
What is data discretization?
Differentiate between star and snowflake schema.
Write short notes on spatial data mining.