Built with SQL | Tableau | Power BI | Excel
A comprehensive analytics solution designed to optimize operations, track guest behavior, and monitor performance metrics across multiple hotel properties.
This project analyzes real-world hospitality booking data to uncover trends in guest preferences, booking behavior, revenue patterns, property performance, and operational efficiency. The data spans multiple cities, room classes, and booking platforms — providing a 360° view of hotel operations.
- SQL (MySQL) – Data preprocessing, transformation, and advanced KPI calculations
- Power BI – Business intelligence dashboards with calculated metrics and slicers
- Tableau – Visual storytelling and drill-down analysis by location, rating, and platform
- Excel – Pivot-based dashboards and exploratory data analysis (EDA)
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Hospitality.sql– SQL script for:- Revenue, rating, and booking trend analysis
- Stay duration, cancellation rate, utilization, and lead time KPIs
- Aggregations by city, room class, platform, and property
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Hospitality.pptx– Final presentation deck includes:- Hospitality industry overview
- Sector-wise breakdown, trends, and challenges
- Final dashboards from Excel, Power BI, and Tableau
- Key insights and takeaways
| Tool | Dashboard Types | Description |
|---|---|---|
| Excel | Dashboard 1, 2 | Booking and rating analysis with slicers by city and room class |
| Tableau | Dashboard 1, 2 | Guest behavior, average stay, ratings, and capacity analytics |
| Power BI | Dashboard 1, 2 | Revenue KPIs, booking lead time, cancellations, and platform-wise reporting |
- Mumbai has the highest room capacity and loyal customer base
- Elite rooms have the longest stay duration; Presidential rooms show high ratings
- Taj Palace leads in bookings while Taj Seasons underperforms in ratings
- UPI and Cash are top payment methods across successful bookings
- Booking cancellations caused significant revenue losses; some platforms showed high cancellation rates
- Operations: Optimize room allocation, reduce cancellations, and monitor utilization
- Customer Experience: Improve service quality by tracking ratings and feedback trends
- Marketing: Identify best-performing platforms and seasonal trends for promotions
- Revenue Management: Analyze stay duration, booking lead times, and payment behavior
- Normalizing inconsistent rating values and booking statuses
- Designing visualizations that balance operational and strategic KPIs
- Creating custom fields for calculated measures like utilization rate, revenue loss, and lead time
- Handling missing values and aligning keys across dimension tables
💡 Want to explore the files?
Feel free to reach out and I’ll be happy to share:
- ✅ Tableau files (.twbx)
- ✅ Power BI files (.pbix)
- ✅ Excel dashboards (.xlsx)
📧 Email: 294sumitkumarsingh@gmail.com
🔗 LinkedIn: linkedin.com/in/sumitkumarss
💻 GitHub: github.com/sumit9000