B.TechSemester 52024-25Data AnalyticsBCS052
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Data Analytics (BCS052) - AKTU Question Paper 2024-25

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 2024-25. 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:2024-25
University:AKTU / UPTU

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Questions Asked in 2024-25

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

Section AAttempt all questions in brief. 2 x 07 = 14
  • a
    Differentiate between Predictive and Prescriptive Data Analyti cs
  • b
    Define the term data lake, dat a base and data warehouse
  • c
    Explain the concept of Outliers. 2 K 2
  • d
    Describe the concept of Lasso Regression
  • e
    Differentiate between Steam Processing and Traditional Data Processing
  • f
    Write the two limitations of K-Mean
  • g
    Discuss the various categories of clustering techniques
Section BAttempt any three of the following: 07 x 3 = 21
  • a
    Explain the different categories of data analytics with examples
  • b
    Explore PCA. Given data = {4, 8, 13, 7; 11, 4, 5, 14}. Compu te the principal component using PCA algorithm. Also use PCA to reduce dimension from 2 to 1
  • c
    E x p l o r e t h e t e r m - M a r k e t B a s k e t A n a l y s i s . I s i t s u p e r v i s e d or unsupervised? Determine how would a company use market basket analysis to improve its marketing strategies?
  • d
    Differentiate between CLIQUE and ProCLUS clustering
  • e
    Differentiate between NoSQL database and a Relational databa se. Identify when one should use a NoSQL database instead of a rela tional database with a suitable example
Section CAttempt any one part of the following: 07 x 1 = 07
  • a
    Differentiate between Structu red data, Semi-structured data and Unstructured Data
  • b
    Describe Big Data and its characteristics
  • a
    Differentiate between Neural Ne twork and Artificial Neural Network
  • b
    A= {(10,0.2), (20,0.4), (25,0.7), (30,0.9), (40,1), (50,0.4}
    B= {(10,0.4), (20,0.1), (25,0.9), (30,0.2), (40,0.6), (50, 0.6)}
Apply Union, Intersection, Com plement, Bold Union and Bold
Intersection operations on above listed Fuzzy Sets
  • a
    Explain and apply Flajolet-Martin algorithm on the following stream of data to identify unique elements in the stream. Given: h(x)=(6x+1) mod 5
  • b
    D i s c u s s t h e C o n c e p t o f f i l t e r i n g i n D a t a S t r e a m P r o c e s s i n g . Explain Bloom Filtering in detail
  • a
    Cluster the following eight points (with (x, y) representing lo cations) into three clusters: A1(2, 10), A2(2, 5), A3(8, 4), A4(5, 8), A 5(7, 5), A6(6, 4), A7(1, 2), A8(4, 9). Initial cluster centers are A1(2, 10), A4(5
  • 8
    and A7(1, 2). The distance function between two points a = (x1, y1) and b = (x2, y2) is defined as Use K-Means Algorithm to find the three cluster centers after implanting all ei ght points
  • b
    The database has 6 transactions. Assume Support threshold=50%, Confidence= 60% TID Items Bought 10 Beer, Nuts, Diape r 20 Beer, Coffee, Diape r 30 Beer, Diaper, Eggs 40 Nuts, Eggs, Mil k 50 Nuts, Coffee, Diaper, Eggs, Mil k 60 Beer, Nuts, Diape r i) Use Apriori algorithm to find all frequent itemsets. ii) Show all the strong association rules (with support and confidence)
  • a
    Brief about the main components of MapReduce
  • b
    Draw the architecture of HIVE with its features

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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