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https://github.com/nagar2nd/itc-hotels-revenue-analysis-power-bi

The project analyzes ITC Hotels revenue and booking trends using Power BI. It features 4 interactive dashboards focusing on revenue optimization, occupancy trends, booking patterns, and cancellations. The analysis provides actionable insights to enhance operational efficiency and customer satisfaction. For detailed data cleaning and transformation
https://github.com/nagar2nd/itc-hotels-revenue-analysis-power-bi

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The project analyzes ITC Hotels revenue and booking trends using Power BI. It features 4 interactive dashboards focusing on revenue optimization, occupancy trends, booking patterns, and cancellations. The analysis provides actionable insights to enhance operational efficiency and customer satisfaction. For detailed data cleaning and transformation

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README 

        
# ITC Hotels Revenue Analysis Project  



## Overview  

This project aims to explore ITC Hotels' revenue data, focusing on key areas such as revenue optimization, occupancy trends, booking behavior, and cancellations. Using **Power BI**, the analysis is presented through four dashboards designed to provide actionable insights for data-driven decision-making.  

## Report Link :

https://docs.google.com/document/d/1-NsT9RCRKJAKS2Nz3WON2QwjF1kjjC6P/edit?usp=sharing&ouid=107857076080323012434&rtpof=true&sd=true



## Dashboards Overview  

### 1. **Revenue Overview Dashboard**  

   - Key financial metrics such as:  

     - **Total Revenue**: ₹28.57M  

     - **ADR (Average Daily Rate)**: ₹6.49K  

     - **RevPAR (Revenue Per Available Room)**: ₹4.32K  

   - Revenue breakdown across different properties and room classes.  

   - Questions Answered:  

     - Which properties are generating the highest revenue?  

     - How do different room categories contribute to overall revenue?  



### 2. **Occupancy Trends Dashboard**  

   - Visualization of occupancy rates for weekdays (42%) vs. weekends (47%).  

   - Comparison of available vs. occupied rooms for each property.  

   - Seasonal trends impacting room occupancy.  

   - Questions Answered:  

     - Are weekends more popular for bookings than weekdays?  

     - How is occupancy distributed across properties?  



### 3. **Booking Patterns Dashboard**  

   - Analysis of booking lead times and average length of stays.  

   - Monthly trends in booking volumes.  

   - Highlights seasonal variations in customer behavior.  

   - Questions Answered:  

     - What is the average lead time for bookings?  

     - Which months see the highest booking activity?  

     - What are the typical stay durations for guests?  



### 4. **Cancellation Analysis Dashboard**  

   - Monthly cancellations and lost revenue trends.  

   - Retained revenue during cancellations.  

   - Focus on June as the month with the highest cancellations.  

   - Questions Answered:  

     - When do cancellations peak, and how much revenue is lost?  

     - How effectively is revenue retained despite cancellations?  



## Data Cleaning and Transformation  

The analysis was preceded by meticulous data preparation steps, including:  

1. **Revenue Adjustment:**  

   - Calculated retained revenue for canceled bookings.  



2. **Ratings Completion:**  

   - Imputed missing ratings based on average values per property.  



3. **Custom Calendar Table:**  

   - Integrated holiday markers and weekend flags.  



4. **Room Capacity Refinement:**  

   - Adjusted room availability data to match booking patterns.  



For a detailed walkthrough of the data cleaning and transformation process, check the attached **documentation (PDF/Word file)** in the repository.



## Insights & Recommendations  

1. **Revenue Drivers:**  

   - ITC Exotica and ITC Palace are top revenue generators.  

   - Elite rooms have the highest contribution to revenue.  



2. **Occupancy Trends:**  

   - Weekends outperform weekdays, suggesting opportunities for weekday promotions.  



3. **Cancellation Management:**  

   - June’s high cancellation rates require better policies and communication strategies.  



4. **Booking Behavior:**  

   - Short lead times and seasonal trends suggest the need for flexible pricing strategies.  



## Tools & Technologies  

- **Power BI**: Interactive dashboards and visualizations.  

- **DAX**: For creating custom measures and calculated fields.  

- **Excel**: Initial exploration and data preparation.  



## File Structure  

- `ITC Hotels Analysis.pbix`: Power BI file containing the interactive dashboard.  

- `All .csv/`: Includes the raw and cleaned datasets used in the project.  

- `Dashboard-Screenshots/`: Visuals of the dashboards for a quick preview.

- `ITC Hotels Revenue Analysis Report.pdf/`: Detailed report on the cleaning and transformation process.  



## How to Use  

1. Clone the repository:  

   ```bash  

   git clone https://github.com/Nagar2nd/ITC-Hotels-Revenue-Analysis-Power-BI.git