• Proposed: NYC restaurant inspections + Yelp reviews
• Goal: Integrate R + Tableau (via Rserve) for hypothesis testing & visualization
• Pivot: California dataset due to data availability

• File Size Limits → Split files, used SSH key
• Yelp Data Access → Used Yelp Open Dataset
• Dataset Coverage → Pivoted to California data
• JSON Errors → Added try/catch for ingestion
• Outcome: Completed analysis using California resturant inspections + Yelp reviews

California’s restaurant inspection program provides comprehensive health and safety data for food establishments across the state.

How do regulatory compliance and customer experience intersect?

Key Finding: Weak negative correlation (-0.124) - health scores don’t predict Yelp ratings.

Key Finding: Critical violations don’t determine customer ratings.

Key Finding: Very weak positive correlation (0.022) - negligible relationship.

Key Finding: Different grades show distinct patterns, but overlap considerably.

Key Finding: Most restaurants cluster in 3-5 violations with 3-4 star ratings.

Health inspection metrics and Yelp ratings measure different dimensions of quality

• ✓ Minimal relationship between health scores and customer ratings
• ✓ Customer priorities: taste, service, ambiance > sanitation compliance
  
• ✓ Information asymmetry: diners rarely check health scores
• ✓ Rating compression: most restaurants cluster around 3-4 stars

Implications: Both perspectives are valuable but independent tools for assessing restaurant quality.

• LA County Restaurant Inspections (Kaggle) - (https://www.kaggle.com/datasets/meganrisdal/la-county-restaurant-inspections-and-violations)

• Yelp Open Dataset - (https://business.yelp.com/data/resources/open-dataset/)