Hospitality Analysis

Problem Statement

Hotel chains often struggle to track performance across multiple properties, booking channels, and customer segments. Key metrics like occupancy, cancellations, and revenue leakage are fragmented across systems, making it hard for management to identify trends and take quick action. The challenge was to build a centralized analytics solution for better decision-making.

Technical Solution

• Step 1 – Architecture & Approach: Designed an end-to-end BI solution by connecting raw hotel data (bookings, revenue, ratings, occupancy) into Power BI. Data cleaning and transformation were performed, followed by creating a star-schema model for easy reporting.
• Step 2 – Key Algorithms, Libraries & Highlights: • Built DAX measures for KPIs: revenue vs. realized revenue, occupancy %, cancellation %, and average ratings. • Created calculated columns for segmentation by hotel category, city, room type, platform, and day type. • Designed interactive dashboards for drill-down analysis (property → city → room type).
• Step 3 – Deployment & Infrastructure: • Dashboards published to Power BI Service for management access. • Role-based access applied to ensure secure insights sharing. • Enabled scheduled data refresh for near real-time analytics.

Results & Impact

Improved revenue tracking with realized vs. generated revenue visibility.

Technologies Used