This project demonstrates a complete data analytics pipeline for stock market data — from data ingestion and storage to interactive dashboards and business-ready BI reports.
The project showcases:
- Real-world financial data modeling
- KPI calculation using DAX
- Dashboard storytelling
- Tool interoperability (Python → MySQL → Power BI)
- Business-oriented visualization design
| Category | Tools |
|---|---|
| Programming | Python |
| Database | MySQL (XAMPP) |
| Libraries | Pandas, NumPy |
| App Dashboard | Streamlit |
| BI Tool | Power BI Desktop |
| Data Format | CSV (fallback for BI integration) |
| Column | Description |
|---|---|
| id | Unique row identifier |
| ticker | Stock symbol |
| trade_date | Trading timestamp |
| month | Trading month |
| open | Opening price |
| high | Highest price |
| low | Lowest price |
| close | Closing price |
| volume | Trade volume |
| created_at | Data insertion timestamp |
Python (ETL)
↓
MySQL Database
↓
CSV Export
↓
Power BI Dashboard