AD-703-A Data Visualization - Dec 2024 Question Paper

Under each question, How to answer lists the points an answer should cover, outlined by CampusPrep from the syllabus. Check the details against your textbook.

1. 7 Marks
   aExplain Aggregation and Data Integration in visualization with help of example.
   How to answer

   • Define aggregation and data integration in visualization context
   • Explain aggregation levels/types with example
   • Explain integration of heterogeneous sources with example
   • Benefits for visualization performance and insight
2. 7 Marks
   bExplain how you will find missing values in heterogeneous data using k-nearest neighbors?
   How to answer

   • Define missing values in heterogeneous data
   • Outline k-nearest neighbors imputation steps
   • Distance/similarity for mixed data types
   • Example of finding and filling missing value
3. 7 Marks
   aExplain different techniques for Visualizing Complex Data with help of example.
   How to answer

   • Define complex/high-dimensional data visualization need
   • Describe techniques e.g. dimensionality reduction, parallel coordinates, treemaps, network graphs
   • Explain each with example
   • Comparison of when to use which
4. 7 Marks
   bBriefly explain Pixel-Oriented Visualization Techniques and discuss its benefits.
   How to answer

   • Define pixel-oriented visualization concept
   • Explain techniques e.g. recursive pattern, circle segments, spiral
   • Explain how values mapped to colored pixels
   • List benefits for large datasets
5. 7 Marks
   aDiscuss Exploratory data analysis techniques with the help of suitable examples.
   How to answer

   • Define exploratory data analysis (EDA)
   • Describe techniques: summary stats, box plots, histograms, scatter plots, correlation
   • Give suitable examples for each
   • Role in hypothesis generation before modeling
6. 7 Marks
   bExplain the need for Geospatial visualization. List five application where Geospatial visualization is required.
   How to answer

   • Define geospatial visualization and its need
   • Explain handling of location, spatial patterns
   • List five applications requiring it
   • Example for each application
7. 7 Marks
   aWrite code to plot a line chart to depict the run rate of a cricket match from given data using Matplotlib.

   

   How to answer

   • Import matplotlib.pyplot
   • Define Overs [5,10,15,20] and Run [50,90,130,180] lists
   • Use plt.plot, xlabel, ylabel, title, show/grid
   • Complete runnable Python code
8. 7 Marks
   bExplain node-link diagram and force-directed graphs for network visualization.
   How to answer

   • Define node-link diagram for networks
   • Define force-directed layout principle
   • Explain working with example
   • Advantages and limitations
9. 7 Marks
   aExplain t-Distributed Stochastic Neighbor embedding technique with suitable example.
   How to answer

   • Define t-SNE purpose for high-dimensional data
   • Explain steps: similarity, perplexity, KL divergence optimization
   • Give suitable example e.g. MNIST/cluster visualization
   • Advantages and limitations
10. 7 Marks
    bWhat do you mean by Confusion Matrix? Explain step by step that how you will calculate confusion matrix with the given data set?
    How to answer

    • Define confusion matrix and TP,TN,FP,FN
    • Steps to construct from predicted vs actual
    • Show calculation with example dataset
    • Derive accuracy, precision, recall from matrix
11. 7 Marks
    aFor a Given data = $\{ 2, 3, 4, 5, 6, 7 ; 1, 5, 3, 6, 7, 8 \}$, Compute the principal component using PCA Algorithm.
    How to answer

    • State given 2D dataset and PCA steps
    • Compute mean, covariance matrix
    • Compute eigenvalues/eigenvectors
    • Select principal component and projection
12. 7 Marks
    bWhat is big data analysis? Explain how it will help in data visualization.
    How to answer

    • Define big data analysis and its Vs
    • Explain role in handling volume/velocity/variety for visualization
    • Examples of tools/techniques
    • How it improves insight and decision making
13. 7 Marks
    aHow can we effectively visualize the text data? Explain with help of the example.
    How to answer

    • Define challenges of text data
    • Describe techniques: word cloud, frequency bar, sentiment, topic models
    • Explain with example
    • Tools used
14. 7 Marks
    bExplain step by step process of a dashboard creation in Tableau.
    How to answer

    • Define Tableau dashboard purpose
    • List steps: connect data, create sheets, add filters, arrange layout
    • Explain publishing/interactivity
    • Example workflow
15. 14 Marks
    Write a short note on any two :

    1. i)Data cleaning tools
    2. ii)Hierarchical Visualization Techniques
    3. iii)Multivariate data visualization
    4. iv)Data Visualization using R
    How to answer

    • Select any two topics from i-iv
    • Define each with key concepts
    • Explain techniques/tools with example
    • Uses and diagram where relevant