1. Question 1

Ability of generative AI that helps overcome limited data availability:

• ❌ Reduces model complexity

• ❌ Optimizes algorithms

• ❌ Collects data from all resources

• ✅ It creates synthetic data sets and augments existing ones.

Explanation:

Generative AI can produce synthetic data, helping overcome data scarcity.

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2. Question 2

How generative AI helps query databases:

• ✅ It can formulate complex queries, optimize interactions, and adapt to evolving structures.

• ❌ Creates visual content

• ❌ Focuses only on pattern recognition

• ❌ Optimizes small datasets

Explanation:

GenAI assists with natural language → SQL, query optimization, and dynamic schema handling.

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3. Question 3

Generative AI ability used to create compelling narratives:

• ❌ Complex queries

• ❌ Pattern recognition

• ❌ Static templates

• ✅ Generates story elements, highlights key insights, and provides structure.

Explanation:

GenAI can produce storytelling elements and explanations from data.

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4. Question 4

AI engine integrating GenAI + ML + Alteryx platform:

• ✅ AiDIN

• ❌ Haptik

• ❌ Palantir AIP

• ❌ DataRobot

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5. Question 5

Comprehensive DS/ML platform with GenAI capabilities:

• ❌ RapidMiner

• ❌ StyleGAN2

• ❌ Tableau

• ✅ OpenAI’s DALL-E 2

(Used for generative modeling + data augmentation tasks)

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6. Question 6

Most suitable prompt to generate a bar chart showing average sales by area:

• ❌ Sales by area

• ❌ Average sales by area (no chart type)

• ✅ Create a bar chart that shows the average sales by area.

• ❌ Create a bar chart

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7. Question 7

SQL query generated for:
“What is the count of rows in the Boston_house_price dataset?”

• ❌ SELECT COUNT FROM …

• ❌ SELECT COUNT * Boston_house_price

• ✅ SELECT COUNT(*) FROM Boston_house_price

• ❌ SELECT * FROM …

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8. Question 8

How GenAI enhances extraction of insights:

• ❌ Provides representative training set

• ❌ Imputes data

• ❌ Generates SQL queries

• ✅ Identifies hidden patterns, generates hypotheses, and provides personalized insights

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9. Question 9

Task GenAI automates to enhance data preparation:

• ❌ SQL generation

• ❌ Personalized insights

• ✅ Data anomaly detection

• ❌ Pattern identification

Explanation:

GenAI automates anomaly detection during preprocessing workflows.

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10. Question 10

Purpose of Q&A for data:

• ❌ Learn latent code

• ✅ Use ML + NLP to understand questions and provide relevant responses

• ❌ Predict future trends

• ❌ Analyze customer behavior

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🧾 Summary Table

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