B.TechSemester 52023-24Introduction To Data Analytics And VisualizationKDS501
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Introduction To Data Analytics And Visualization (KDS501) - AKTU Question Paper 2023-24

B.Tech · Semester 5 · Free PDF Download

This is the official AKTU Introduction To Data Analytics And Visualization 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

Introduction To Data Analytics And Visualization (KDS501) — extracted question text · 100 marks · 3 Hours

Section AAttempt all q u e s t i o n s i n b r i e f . 2 * 1 0 = 2 0
  • a
    What are the features of Big Data? 1
  • b
    What is decision tree? 1
  • c
    Explain the need of Data Analytics. 2
  • d
    What do you mean by learning rate? 2
  • e
    What is real time analysis? 3
  • f
    Define data Model. 3
  • g
    Discuss Sentiment Analysis. 4
  • h
    List various methods of clustering. 4 (i) Differentiate between Pig and SQL. 5 (j) Write any two visualization tools. 5
Section BAttempt any three o f t h e f o l l o w i n g : 1 0 * 3 = 3 0
  • a
    Discuss Classification of D ata. Explain all the categories in detail with examples. 1
  • b
    Illustrate with example Reg ression and Bayesian modelling. 2
  • c
    Discuss RTAP applications in detail. 3
  • d
    Illustrate with example s CLIQUE and ProCLUS. 4
  • e
    Discuss various visualization techniques with suitable exam ples. 5
Section CAttempt any one p a r t o f t h e f o l l o w i n g : 1 0 * 1 = 1 0
  • a
    Explain the phase of Data a nalytics life cycle in detail. 1
  • b
    Write short note on the following- i. Modern Data analytics tools ii. Application of data analytics
  • a
    Demonstrate any algorithm for counting oneness in a window. 2
  • b
    What are the various stochas tic search methods. Explain in detail with suitable example
  • a
    With the help of suitable example explain prediction error in classification and regression
  • b
    Discuss k-means clustering? Explain its working. Write k-me ans algorithm for partitioning
  • a
    Discuss as a case study – R eal time sentiment Analysis. 4
  • b
    Explain the following- i. Apriori Algorithm ii. Market based modeling
  • a
    Draw and discuss the archite cture of HDFS in detail. 5
  • b
    What are the approaches to in tegrate the human in data exploration process to realize different types of approaches to visual data mining?

Question text is extracted from the official AKTU question paper PDF above. Check the original PDF for equations, diagrams and complete wording. Extracted: 2026-08-23.

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