End-to-end data analytics: Python scarping & automation, MySQL cleaning, Tableau visualization & business insights.
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Complete analysis of Starbucks sales and store performance. Built with Python for data scraping and automation, MySQL for data cleaning, and Tableau for powerful visualizations and business insights.
- Python: Scraping, automation, data processing with Pandas
- MySQL: Data cleaning, transformation, and storage
- Tableau: Advanced dashboards with calculated fields and storytelling
- Collected Starbucks-related data through Python scraping and automation
- Cleaned and organized data in MySQL
- Developed interactive Tableau dashboards
- Interpreted results to support business decisions
- Discovered top performing products and store locations
- Clone this repository
- Install dependencies:
pip install -r requirements.txt - Set up MySQL database and run the SQL scripts in the
sql/folder - Run Python scripts in
src/folder - Open the Tableau workbook (.twbx) in the
tableau/folder
- Add customer segmentation analysis
- Include predictive sales forecasting
- Expand to more locations and metrics