| marp | theme | size | paginate | header | footer |
|---|---|---|---|---|---|
true |
default |
58140 |
true |
Statistics Canada | Statistique Canada |
- Unified environment: JupyterLab, RStudio, VS Code
- Multi-language support: Python, R, and SAS
- Built on Kubeflow & Kubernetes for scalability
- Cost Efficiency: Pay only for resources you use
- Flexibility: Create workspaces of any size
- Open Source Foundation: Eliminate expensive licenses
- Container-based workflow system on Kubernetes
- Simplifies environment creation and experiment tracking
- Enables reproducible data science at scale
- Access: https://zone.statcan.gc.ca with enterprise credentials
- Users: 2,000+ onboarded, 120+ concurrent daily
- Performance: Auto-scaling handles peak loads efficiently
- Start Small: Scale resources as needed to control costs
- Smart Data: Use databases instead of copying data
- Version Control: Track changes with Git for reproducibility
- JupyterLab: Interactive computing with rich visualizations
- RStudio: Dedicated R environment with statistical tools
- VS Code: Full-featured editor with multi-language support
- Built-in Compatibility: Run SAS code without expensive licenses
- Cost Savings: Reduce licensing fees while preserving investments
- Migration Path: Gradual transition to modern open-source tools
- Legacy Systems: Performance issues with old SMB shares
- Learning Curve: Training needed for containerized environments
- Resource Planning: Requires careful allocation for large deployments
- Pipeline Modernization: Transforming cronjobs into Kubeflow Pipelines
- Enhanced Visualization: New tools for sharing graphical analysis
- Continuous Innovation: Expanding capabilities based on user needs