This project demonstrates an end-to-end data analytics pipeline built using Medallion Architecture in Snowflake.
The goal is to analyze hotel booking data to uncover insights related to:
- Revenue trends
- Cancellation behavior
- Seasonal demand
- Operational performance
The solution follows a structured data engineering approach:
Bronze → Silver → Gold
🔹 Bronze Layer (Raw Data)
- Raw CSV ingested into Snowflake
- No transformations applied
- Maintains original schema
- Used for traceability & audit
🔹 Silver Layer (Cleaned & Standardized)
Applied transformations:
- Trimmed string columns
- Standardized names
- Converted date columns
- Handled null values
🔹 Gold Layer (Business Aggregations)
- Business-ready views created for reporting.
💰 Revenue Analysis
- Total Revenue
- Monthly Revenue Trend
- Revenue by City
❌ Cancellation Rate
📈 Bookings Analysis
- Total Bookings
- Bookings by Room Type
- Booking analysis by Status
- Average number of days stayed per City
- Peak booking months identified
- Higher cancellation rates observed for long lead times
- City hotels showed higher ADR than resort hotels
- Repeat guests contributed significantly to stable revenue
- Snowflake
- SQL
- Medallion Architecture
- Data Modeling
- Aggregation & KPI Design
/sql
bronze_layer.sql
silver_layer.sql
gold_layer.sql
/dataset
hotel_bookings_raw.csv
/images
dashboard_screenshots.png
README.md
- Implemented Medallion Architecture in Snowflake
- Built data pipelines using layered modeling
- Practiced advanced SQL transformations
- Designed star schema
- Created business KPIs from raw data
- Improved analytical storytelling
- Automate pipeline using Snowflake Tasks
- Add Streams for incremental loading
- Integrate BI tool (Power BI / Tableau)
- Implement performance optimization using clustering