B.TechSemester 52023-24Data AnalyticsKCS051

Data Analytics (KCS051) - AKTU Question Paper 2023-24

B.Tech · Semester 5 · Free PDF Download

This is the official AKTU Data Analytics Previous Year Question Paper for B.Tech Semester 5, academic session 2023-24. Published by Dr. A.P.J. Abdul Kalam Technical University (AKTU/UPTU), Lucknow. Free PDF download — no login required.

Course:B.Tech

Semester:Semester 5

Session:2023-24

University:AKTU / UPTU

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Questions Asked in 2023-24

Data Analytics (KCS051) — complete question paper · 100 marks · 3 Hours

Section AAttempt all q u e s t i o n s i n b r i e f . 2 x 10 = 20

a
How have advancements in techno logy contributed to the scalabi lity of analytics?
b
What are the sources of data in the context of data analytics? 2
c
Elaborate on the mathematical f oundations of support vector machines. 2
d
Discuss the advantages of usin g Bayesian methods in real-world applications
e
Elaborate on the methods used f or filtering streams in real-time analytics. 2
f
What considerations should be t aken into account when implemen ting sampling techniques for stream data?
g
How do stream-based algorithms d iffer from batch processing algorithms in the context of frequent itemset mining?
h
What are the challenges associated with implementing Apriori i n scenarios with limited available memory? i. Explain the role of Hive i n the Hadoop ecosystem. 2 j. How does the MapReduce framewo rk facilitate distributed processing? 2

Section BAttempt any three o f t h e f o l l o w i n g : 10 x 3 = 30

a
Describe the characteristics of data that are relevant in th e field of data analytics. How do these characteristics impact the analysis process?
b
Explain the concept of Bayesia n networks and their applications in modeling probabilistic relationships among variables. Discuss how Bayesian networks can be constructed from data and used for reasoning under uncertainty
c
Provide an overview of Real-tim e Analytics Platforms applica tions, emphasizing their role in processing continuous data streams. How do these platforms support the development of real-time analytics solutions?
d
Compare the strengths and wea knesses of hierarchical cluster ing and K- means clustering. Under what circumstances would one technique be preferred over the other, and why?
e
Discuss the concept of sharding in the context of NoSQL data bases. How does sharding contribute to scalability, and what challenges does it address?

Section CAttempt any one p a r t o f t h e f o l l o w i n g : 10 x 1 = 10

a
Explain the concept of generalization in neural networks. Ho w does it relate to the trade-off between bias and variance, and what strategies can be employed to enhance generalization performance?
b
Provide a detailed explanation of how fuzzy logic is used to extract models from data. Discuss the advantages of fuzzy modeling in capturin g uncertainty and handling imprecise information in comparison to traditional crisp models
a
In the context of stream data, explain different approaches for counting distinct elements. How do these methods address challenges associated with continuously changing data?
b
Describe the concept of counting uniqueness in a window in t he context of stream processing. How does this relate to measuring the freque ncy and uniqueness of elements within a specified time frame?
a
Provide an in-depth compari son between the CLIQUE and ProCLU S clustering algorithms. How do th ese methods handle challenges s uch as noise, outliers, and varying cluster shapes?
b
Explore the challenges and considerations when performing cl ustering in non-Euclidean spaces. How do distance metrics and similarity me asures differ in non-Euclidean environmen ts, and what impact does this have on clustering outcomes?
a
How do interactive technique s contribute to the exploration and analysis of large datasets? Provide examples of systems or tools that lever age interactive approaches effectively
b
Discuss the role of NoSQL databases in handling unstructured data. Provide examples of scenarios where NoSQL databases outperform traditio nal relational databases
a
Differentiate between analysis and reporting in the context of data analytics. How do these two aspects contribute to the overall understanding of data?
b
Explore modern data analytic tools and their functionalities. How have these tools transformed the landscape of data analytics?

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.

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