MCASemester 32024-25Data Warehousing Data MiningKCA012

Data Warehousing Data Mining (KCA012) - AKTU Question Paper 2024-25

MCA · Semester 3 · Free PDF Download

This is the official AKTU Data Warehousing Data Mining Previous Year Question Paper for MCA Semester 3, academic session 2024-25. Published by Dr. A.P.J. Abdul Kalam Technical University (AKTU/UPTU), Lucknow. Free PDF download — no login required.

Course:MCA

Semester:Semester 3

Session:2024-25

University:AKTU / UPTU

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Questions Asked in 2024-25

Data Warehousing Data Mining (KCA012) — complete question paper · 100 marks · 3 Hours

Section AAttempt all questions in brief. 2 x 10 = 20

a
Though we can work with databas e, why Data Warehouse is required?
b
What do you mean by data warehouse schema?
d
How data mining is different from data warehousing
e
Discuss difference between OLTP and OLAP
f
Give the reason for noisy data?
g
Difference between clustering and classification
h
Discuss basic assumption in Naïve Bayes Classifiers. 4 K2 i. What do you mean by data visualization? 5 K2 j. Explain Spatial Data with example

Section BAttempt any three of the following: 10 x 3 = 30

a
Describe Three-tier data war ehouse architecture with a neat diagram
b
Explain Star schema & snowflak e schema with suitable example
c
Discuss K means algorithm with proper example
d
Describe different types of O LAP operations with examples. 4 K 2
e
Explain web mining in detail

Section CAttempt any one part of the following: 10 x 1 = 10

a
Why data cleaning is required? Discuss the methods of data cleaning
b
Describe in detail about the H ardware and Operating Systems for Data Warehousing
a
Discuss the KDD process in detail
b
Assume we have the following dataset of 6 samples, each with 2 features, and a binary class label: Sample Age Income Class 1 25 High No 2 30 High No 3 35 Medium Yes 4 40 Medium Yes 5 50 Low Yes 6 60 Low No The entropy of the entire data set is 1, Entropy of the splitti ng attribute Age is 1, Weighted Entropy of the splitting attribute Age is 1, Entropy of the splitting attribute Income is 0, Weighted Entropy of the splitting attribute Income is .33. Draw the decision tree
a
How distance-based technique i s used for data mining?
b
Transaction List of Items Support = 50%, Confidence = 60% Generate association rule for given items using Apriori Algorithms
a
Discuss Hierarchical Clustering in detail
b
Write notes on i) STING ii) CLIQUE
a
Discuss in detail the security issues in Data Warehousing. 5 K 2
b
What is temporal mining? Explain in detail

Question text is extracted from the official AKTU question paper PDF above. Hindi translations are omitted — every question is printed in English in the original paper. Last verified: 2026-08-23.

Repeated Questions — KCA012

Questions that appeared in more than one session, found by comparing 4 years of Data Warehousing Data Mining papers (2021-22, 2022-23, 2023-24, 2024-25)

How data mining is different from data warehousing

Appeared in: 2023-24 · 2024-25

Discuss difference between OLTP and OLAP

Appeared in: 2022-23 · 2024-25

Describe different types of O LAP operations with examples. 4 K 2

Appeared in: 2021-22 · 2024-25

Discuss in detail the security issues in Data Warehousing. 5 K 2

Appeared in: 2023-24 · 2024-25

Data Warehousing Data Mining — Other Year Papers

AKTU Data Warehousing Data Mining PYQs from other sessions

Data Warehousing Data Mining2021-22 Data Warehousing Data Mining2022-23 Data Warehousing Data Mining2023-24 Data Warehousing Data Mining2024-25 Data Warehousing Data Mining2021-22 Data Warehousing Data Mining2022-23

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