Add advanced examples: pro-dev quick start (4-table system) and data science risk assessment pipeline

Pro-dev quick start (prodev_quick_start.py):
- Create 4 custom tables with columns and relationships
- Populate with sample data using DataFrame CRUD
- Query, analyze, update, and delete records
- Includes pandas vs dict/list rationale

Data science risk assessment (datascience_risk_assessment.py):
- 5-step pipeline: Extract -> Analyze -> LLM Summarize -> Write-back -> Report
- Statistical risk scoring with pandas/numpy
- 3 LLM provider options: Azure AI Inference, OpenAI, GitHub Copilot SDK
- Template-based fallback when no LLM configured
- Optional matplotlib visualization

Author: Saurabh Badenkal