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Case Study: Data Analysis in Databricks

Elliot Zhu

Data Scientist

Exploring the Airbnb dataset

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Key Achievements:
- Connected to the Airbnb dataset using Databricks
- Conducted data quality assessments to ensure accurate and reliable insights
- Wrote SQL queries to explore room types, pricing, and availability trends

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Outcome: Prepared a clean, structured dataset for further analysis

Image of the curated dataset for Airbnb.

Uncovering key patterns and relationships

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Key Achievements:
- Applied window functions to rank listings and find top performers
- Engineered features such as:
  - Price-to-review ratio
  - Host density
- Aggregated metrics to analyze:
  - Total earnings
  - Average prices
  - Service fee trends

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Outcome: Uncovered critical insights to guide pricing strategies and operational improvements.

Image of the final dashboard for Airbnb.

Bringing insights to life

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Key Achievements:
- Designed interactive dashboards in Databricks
- Created visualizations:
  - Trends: Average price, review rate, and availability
  - Correlations: Scatter plots for price vs review rate, availability, and fees
  - Heatmaps: Listing counts by neighborhood and room type

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Leveraged Databricks AI & BI capabilities:
- Scalable data processing for large datasets
- Interactive and real-time visualizations for deeper exploration
Outcome: Enabled stakeholders to explore insights dynamically and drive data-driven decisions

Thank you

Case Study: Data Analysis in Databricks

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