This project centers on developing an interactive Power BI dashboard to analyze and visualize hospitality performance data sourced from a structured CSV dataset. The dataset contains key attributes such as hotel names, locations, booking dates, room categories, occupancy rates, revenue, average daily rate (ADR), customer satisfaction scores, and seasonal trends. Data preprocessing and cleaning were performed within Power Query to remove inconsistencies, handle missing values, and ensure accuracy in reporting. Analytical measures and KPIs were created using DAX (Data Analysis Expressions), including metrics such as:

The dashboard begins with a structured CSV dataset containing key hotel data — locations, booking dates, occupancy rates, revenues, and customer metrics. Inside Power Query, I cleaned and standardized the data to eliminate inconsistencies and ensure integrity across all tables. After establishing accurate relationships between dimension and fact tables, I used DAX to calculate crucial KPIs such as Occupancy %, Average Daily Rate (ADR), and Revenue per Available Room (RevPAR), enabling dynamic comparisons across hotels and time periods. The dashboard is designed for business stakeholders to explore performance interactively — they can filter by property, region, or time period to instantly view how metrics like Occupancy %, Average Daily Rate (ADR), and Revenue per Available Room (RevPAR) fluctuate over time. The dashboard helps management identify trends, detect underperforming areas, and plan marketing or pricing strategies accordingly. Each visualization transforms complex data into an actionable narrative, enabling informed decision-making and empowering business teams to track performance, improve operations, and forecast revenue more effectively.