https://github.com/shubhamgoyal575/hospitality-domain
https://github.com/shubhamgoyal575/hospitality-domain
Last synced: 23 days ago
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- Host: GitHub
- URL: https://github.com/shubhamgoyal575/hospitality-domain
- Owner: shubhamgoyal575
- Created: 2024-04-18T12:34:00.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-18T12:38:41.000Z (over 1 year ago)
- Last Synced: 2024-04-18T14:28:24.721Z (over 1 year ago)
- Size: 3.99 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# AtliQ Grands Revenue Analysis
## Project Overview
AtliQ Grands, a prestigious chain of five-star hotels across India, has been a key player in the hospitality industry for the past 20 years. Facing market share and revenue losses due to strategic moves by competitors and ineffective management decisions, AtliQ Grands aims to regain its market position. The managing director has decided to incorporate "Business and Data Intelligence" to drive this revival. Without an in-house data analytics team, AtliQ Grands has enlisted a third-party service provider to derive insights from historical data.
## Objectives
-Analyze historical revenue data to identify trends and insights.
-Develop metrics according to the provided metric list.
-Design a dashboard based on the stakeholder-provided mock-up.
-Generate additional relevant insights not specified in the metric list/mock-up.
## Tools and Technologies
-Data Analysis: Excel,Power Bi
-Data Visualization: Power BI
-Dashboard Design: Power BI
## Project Structure
### 1. Data Analysis
-Data Collection: Gather and understand the sample data provided.
-Data Preparation: Clean and preprocess the data for analysis.
-Metric Calculation: Develop metrics as per the provided list.
### 2. Dashboard Design
-Mock-up Dashboard: Design the dashboard according to the provided mock-up.
-Visualization: Use charts, graphs, and other visual elements to present data.
-Interactivity: Ensure the dashboard is interactive and user-friendly.
### 3. Insight Generation
-Trend Analysis: Identify trends and patterns in the historical data.
-Performance Metrics: Calculate key performance metrics.
-Additional Insights: Generate additional insights beyond the provided metrics.
### 4. Presentation Preparation
-Summary of Findings: Summarize the key insights and findings from the analysis.
-Visualization: Create visual elements to support the findings.
-Recommendations: Provide actionable recommendations based on the analysis.
## Files and Resources
-Sample Data: Historical revenue data for analysis.
-Mock-up Dashboard: Design template provided by stakeholders.
-Metric List: List of metrics to be calculated.