AD-404 Data Science - Jun 2023 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 the difference between structured and unstructured data.
   How to answer

   • Define structured data with schema, examples
   • Define unstructured data with examples
   • Compare on format, storage, processing, tools
   • Give application examples
2. 7 Marks
   bDefine Data Science? Explain the applications of Data Science.
   How to answer

   • Define Data Science as interdisciplinary field
   • Explain components: statistics, ML, domain
   • List applications: healthcare, finance, marketing, etc.
   • Give example use-case for each
3. 7 Marks
   aBriefly explain about descriptive data analysis.
   How to answer

   • Define descriptive analysis and its goal
   • Explain measures: central tendency, dispersion
   • Mention summary statistics and visualization
   • Give example
4. 7 Marks
   bWhat is data visualization? Discuss box plots and Histograms.
   How to answer

   • Define data visualization and its importance
   • Explain box plot: quartiles, outliers, structure
   • Explain histogram: bins, distribution shape
   • Compare use-cases with diagram
5. 9 Marks
   aDiscuss the usage of VLOOKUP and XLOOKUP operations used for data analysis.
   How to answer

   • Define VLOOKUP syntax and working
   • Define XLOOKUP syntax and advantages
   • Compare lookup direction, defaults, error handling
   • Give example usage in data analysis
6. 5 Marks
   bWhat is pivoting? Explain the types of pivoting.
   How to answer

   • Define pivoting in data analysis
   • Explain types of pivoting
   • Mention pivot tables use-case
   • Give example
7. 6 Marks
   aWhat is random forest? Explain with suitable example.
   How to answer

   • Define random forest as ensemble of decision trees
   • Explain bagging and voting mechanism
   • Outline steps with example dataset
   • Mention advantages and applications
8. 8 Marks
   bDiscuss visualization tools Pie chart and Bar chart in python.
   How to answer

   • Introduce Python visualization libraries
   • Explain pie chart usage and code
   • Explain bar chart usage and code
   • Compare when to use each
9. 9 Marks
   aGive a brief overview on Business Intelligence and Business Intelligence Tools.
   How to answer

   • Define Business Intelligence and its need
   • Explain BI architecture/process
   • List BI tools: Power BI, Tableau, etc.
   • Give business use-cases
10. 5 Marks
    bWrite a short note on the role of Data Scientist.
    How to answer

    • Define Data Scientist role
    • Explain responsibilities: cleaning, modeling, communication
    • Mention required skills
    • Explain business value
11. 9 Marks
    aWhat is Data Wrangling in data science and why it is important? Explain.
    How to answer

    • Define data wrangling/cleaning
    • Explain steps: discovery, structuring, cleaning, enriching
    • Explain importance for quality analysis
    • Give example tools and workflow
12. 5 Marks
    bGive an overview of Macros with suitable example.
    How to answer

    • Define Macros and its purpose
    • Explain how to record/create macros
    • Give suitable example with steps
    • Mention benefits and limitations
13. 7 Marks
    aExplain the following? i) Data Frame ii) Gradient Boosting
    How to answer

    • Define Data Frame structure and features
    • Define Gradient Boosting principle
    • Explain working with example
    • Mention libraries and use-cases
14. 7 Marks
    bWhat are the ethical issues in Business Intelligence? Discuss.
    How to answer

    • Define Business Intelligence ethics context
    • List issues: privacy, bias, transparency, ownership
    • Discuss each with example
    • Suggest best practices
15. 14 Marks
    Explain any two of the following:

    1. a)Exploratory Analysis
    2. b)Data Validation Techniques
    3. c)Regular Expression
    4. d)Data Analysis vs. Data Scientist
    How to answer

    • Select any two topics from list
    • Define each concept clearly
    • Explain key steps/techniques with example
    • Mention applications and diagram if needed