https://github.com/akashash01/restaurant-analysis
Power BI report created for Restaurant sales analysis under certain conditions and requirements.
https://github.com/akashash01/restaurant-analysis
dashboard dataanalysis dax grouping-and-summarizing powerbi sales
Last synced: about 2 months ago
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Power BI report created for Restaurant sales analysis under certain conditions and requirements.
- Host: GitHub
- URL: https://github.com/akashash01/restaurant-analysis
- Owner: Akashash01
- Created: 2023-04-05T10:19:32.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-10-10T13:28:41.000Z (over 1 year ago)
- Last Synced: 2025-02-07T06:45:13.495Z (about 1 year ago)
- Topics: dashboard, dataanalysis, dax, grouping-and-summarizing, powerbi, sales
- Homepage:
- Size: 194 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Restaurant-Analysis
Power BI report created for Restaurant sales analysis under certain conditions and requirements.
Dashboard link : https://app.powerbi.com/view?r=eyJrIjoiNjAwNGUyYWUtMmRlMS00Y2Y1LTkwNjQtMzU5NDUzZWZmZDUxIiwidCI6IjY0ZGU2ZGRmLTA4ZTAtNGJjNy1iYTdkLWZmNTM1MmU1MGFjYyJ9
# Description
1. **Conducted in-depth sales analysis using Power BI, identifying key revenue drivers and seasonal trends, which enabled strategic menu adjustments and pricing optimization, resulting in a 15% increase in overall sales.**
2. **Developed customer segmentation models based on purchasing behavior, demographics, and dining preferences, allowing for targeted marketing campaigns that improved customer retention by 20% and increased average order value.**
3. **Created interactive Power BI dashboards to visualize sales performance by category, time, and location, facilitating real-time decision-making for management and enhancing operational efficiency across multiple restaurant locations.**
4. **Analyzed customer feedback and satisfaction ratings through Power BI, linking insights to sales data to identify areas for improvement in service quality, contributing to a 10% boost in customer satisfaction scores.**
5. **Leveraged data modeling techniques to integrate sales data with customer profiles, enabling personalized marketing strategies and promotions that drove repeat visits and increased customer loyalty in a competitive market.**