🔍 Purpose:
To automate the collection and analysis of wine auction data by scraping live listings from an auction website and visualizing key metrics in an interactive Power BI dashboard
🔗 View on GitHub
What I Built:
A Python-based web scraper using Selenium and BeautifulSoup that extracts detailed wine lot data (name, vintage, region, bottle size, estimates, hammer prices). The scraped data is stored in a database, which is then connected to a Power BI dashboard to track bidding trends, estimate ranges, and sale outcomes.
Use Cases:
- Time-saving Automation: Helps eliminates the need for manual data collection, ensuring faster updates and higher efficiency.
- Real-Time Insights: Enables timely tracking of bidding activity and market behavior.
- Data Accuracy and Consistency: Reduces human error and ensures uniform data structure for reliable analysis.
- Market Intelligence: Identifies trends in hammer prices, estimate accuracy, and performance by region or vintage which valuable for wine investors and auctioneers.
- Scalability: Can be easily extended to scrape multiple auction houses or additional wine attributes.
- Interactive Reporting: Power BI visualizations make it easy to explore data, uncover patterns, and present insights to stakeholders in an intuitive format.
📊View Power BI Dashboard
Script
