Graded Assignment: Requirements Elicitation and Documentation with Generative AI :Generative AI: Revolutionizing Business Analysis Techniques (IBM Business Analyst Professional Certificate) Answers 2025

Question 1

Which aspect of AI-powered requirements gathering involves understanding relationships between data points?

❌ Data visualization and presentation
❌ Data encryption and security
❌ Data storage and retrieval
✅ Data analysis and pattern recognition

Explanation:
Understanding relationships, trends, and dependencies between data points is achieved through data analysis and pattern recognition.

Question 2

How do generative AI tools assist in structuring requirements?

✅ By converting unstructured text into standardized requirement formats with unique IDs and priorities
❌ By generating random data sets for analysis
❌ By eliminating redundant data entries
❌ By creating automated project timelines

Explanation:
Generative AI can transform free-text inputs into structured, traceable requirements.

Question 3

How do generative AI tools differ from traditional requirements extraction methods?

❌ AI tools require more time than manual methods
❌ Traditional methods identify patterns better
✅ Generative AI tools automate the process, reducing manual effort
❌ Traditional methods are more accurate

Explanation:
AI significantly automates extraction, saving time and effort compared to manual analysis.

Question 4

Key benefit of using generative AI for requirements extraction?

✅ Increased speed and efficiency in processing large volumes of data
❌ Reduced need for technical expertise
❌ Elimination of human oversight
❌ Interpreting emotional tone

Explanation:
AI processes large datasets quickly, improving efficiency—but still needs human review.

Question 5

Primary challenge of manual process mapping that AI helps avoid?

❌ Difficulty understanding business objectives
❌ Expensive software licenses
❌ Lack of collaboration
✅ Inconsistent notation in diagrams

Explanation:
AI ensures standardized notation, reducing inconsistency across process diagrams.

Question 6

How can generative AI optimize business process models?

❌ Replace BA oversight
✅ Automatically generate process maps and suggest improvements
❌ Maintain maps without humans
❌ Conduct interviews manually

Explanation:
AI can draft process models and highlight optimization opportunities, with BA validation.

Question 7

What role does AI play in creating comprehensive process models?

❌ Replaces modeling techniques
❌ Focuses only on customer feedback
✅ Assists in analyzing data to identify patterns and suggest improvements
❌ Fully automates modeling

Explanation:
AI supports analysts by identifying insights; it does not replace human judgment.

Question 8

How does generative AI enhance exploration of complex datasets?

✅ By enabling intuitive queries through natural language
❌ Automatically cleaning all data
❌ Providing predefined reports
❌ Eliminating validation

Explanation:
Natural language querying allows users to explore data easily without complex queries.

Question 9

Major challenge generative AI helps overcome in data analysis?

✅ The steep learning curve of traditional data analysis tools
❌ Need for high computational power
❌ Cost of data
❌ Team collaboration needs

Explanation:
AI lowers the skill barrier, making data analysis accessible to non-technical users.

Question 10

How does generative AI improve stakeholder understanding of visualizations?

❌ Making visuals entertaining
❌ Removing complexity entirely
❌ Making all visuals identical
✅ Customizing visualizations to stakeholder preferences and understanding

Explanation:
Tailored visuals ensure clear communication for different stakeholder groups.

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