Behavioral analytics pipeline for casino player data with churn prediction.

• ETL Pipeline: Extract, transform, load player activity data
• Engagement Analytics: Daily active players, retention, VIP metrics
• Betting Analysis: Game performance, win/loss ratios, high rollers
• Session Analytics: Duration patterns, peak hours, device usage
• Churn Prediction: ML model for identifying at-risk players
• Tableau Export: CSV exports for Tableau dashboards
• REST API: FastAPI endpoints for real-time queries

pip install -r requirements.txt

python -c "from src.etl.pipeline import run_pipeline; run_pipeline(10000, 100000)"

uvicorn src.api.main:app --reload

streamlit run dashboards/app.py

• Players: Player dimension table
• PlayerActivities: Activity fact table
• ChurnScores: Churn predictions
• EngagementMetrics: Daily metrics

• Python 3.11+
• SQLAlchemy (SQLite/Snowflake)
• Scikit-learn
• FastAPI
• Streamlit
• Plotly

MIT