B.TechSemester 52025-26Data AnalyticsBCS052
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Data Analytics (BCS052) - AKTU Question Paper 2025-26

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 2025-26. 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:2025-26
University:AKTU / UPTU

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Questions Asked in 2025-26

Data Analytics (BCS052) — complete question paper · 70 marks · 3 Hours

Section AAttempt all questions in brief. 02 x 7 = 14
  • a
    What is Data Analytics?
  • b
    List any two characteristics of Big Data
  • c
    What is regression analysis?
  • d
    What is a data stream?
  • e
    Define frequent itemset
  • g
    What is Exploratory Data Analysis (EDA)?
Section BAttempt any three of the following: 07 x 3 = 21
  • a
    Explain the phases of the Data Analytics Lifecycle with objectives of each phase
  • b
    The following data represents study hours (X) and scores (Y): (i) Find the linear regression equation. (ii) Predict Y when X = 7
  • c
    Explain Bayesian modeling and the role of prior and posterior probabilities
  • d
    A data stream generates 120,000 records per minute. If only 35% data is retained using a decaying window, calculate the number of records retained per minute and justify the use of windowing
  • e
    Explain the importance of frequent itemset mining in market basket analysis
Section CAttempt any one part of the following: 07 x 1 = 07
  • a
    Explain Support Vector Machines (SVM) with the concept of margin and support vectors
  • b
    A dataset has eigenvalues: 4.5, 2.8, 1.2, 0.4, 0.1. (i) Calculate percentage variance of each component. (ii) Determine the number of components required to retain 90% variance
  • a
    A sliding window of size 200 slides by 50 elements. Calculate the number of windows formed after processing 1,000 elements and explain its impact on latency
  • b
    Design a Real -Time Analytics Platform for social media sentiment analysis showing major components
  • a
    Given transactions:
    T1 {A, B, C}, T2 {A, B}, T3 {A, C}, T4 {B, C}, T5 {A, B, C}
If minimum support = 60%, find all frequent item sets and show pruning
  • b
    Compare hierarchical clustering and K -means clustering with suitable applications
  • a
    Explain the working of MapReduce with intermediate key –value pairs
  • b
    Design a Hadoop -based framework for storing and processing large -scale data
  • a
    For the dataset {12, 15, 20, 22, 25, 30}, calculate mean and standard deviation and comment on data spread
  • b
    Design an R -based workflow for analyzing unstructured text data

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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