This project involves analyzing and visualizing hotel revenue and occupancy data using Power BI. The data was obtained from five CSV files including dim_date, dim_rooms, dim_hotels, fact_bookings, and fact_aggregated_bookings.

The first step involved data cleansing and exploration using SQL Server Management Studio (SSMS). This was done to ensure that the data was consistent, accurate, and relevant for the analysis. The data cleansing process involved identifying and handling missing values, outliers, duplicates, and incorrect data types.

After the data cleansing process was completed, a query was created to extract the necessary data for visualization in Power BI. The query involved joining the relevant tables to obtain the required data fields such as hotel revenue, occupancy rates, and booking platform statistics. The query was optimized to ensure that it was efficient and fast.

Once the data was extracted, it was loaded into Power BI for visualization. The Power BI dashboard was designed to provide insights into the hotel revenue and occupancy data. The dashboard included various visualizations such as bar charts, line charts, and tables. The visualizations included information about revenue and occupancy rates across different room categories, booking platforms, check-in dates, and hotels. Additionally, trends in revenue and occupancy rates over time were also included in the dashboard.

Overall, this project provides a comprehensive analysis of hotel revenue and occupancy rates using data from multiple sources. The analysis and visualization were done using SQL Server Management Studio and Power BI, respectively. The final output is a dashboard that provides valuable insights into the hotel's performance and provides recommendations for improving performance during low seasons or economic downturns.

https://public.tableau.com/app/profile/mukesh.ale/viz/Book1_16839223767660/Dashboard1