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Starts 7 June 2025 19:57
Ends 7 June 2025
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Observable Framework - A New Open-Source Static Site Generator for Data Visualization
Discover how Observable Framework revolutionizes data visualization development with its open-source static site generator, enabling custom dashboards and seamless data workflow integration.
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Overview
Discover how Observable Framework revolutionizes data visualization development with its open-source static site generator, enabling custom dashboards and seamless data workflow integration.
Syllabus
- Introduction to Observable Framework
- Setting Up Your Environment
- Understanding the Basics
- Building a Static Site
- Leveraging Data Visualization
- Dashboard Development
- Data Workflow Integration
- Advanced Customizations
- Deployment and Maintenance
- Case Studies and Real-World Examples
- Conclusion and Next Steps
Overview of the Observable ecosystem
Key features of the Observable Framework
Comparison with other static site generators
Installing Node.js and npm
Installing the Observable Framework
Setting up a development environment
Observable notebooks: Concepts and structure
Basic syntax and cell types
Data binding and reactivity
Creating a basic Observable page
Integrating static content with dynamic components
Structuring a multi-page static site
Introduction to data visualization libraries supported by Observable
Creating and customizing visualizations with D3.js
Incorporating Vega-Lite for rapid chart development
Designing interactive dashboards
Workflow integration with real-time data sources
Custom user interface components
Connecting external data sources
Managing data updates and synchronization
Automation of data processing tasks
Extending functionalities with custom plugins
Performance optimization techniques
Security considerations in static site deployment
Best practices for deploying Observable sites
Continuous integration and delivery (CI/CD) pipelines
Monitoring site performance and updates
Analysis of industry applications using Observable Framework
Best practices learned from real implementations
Review of key concepts and skills
Resources for further learning
Community support and contribution opportunities
Subjects
Data Science