Realtime Teamwork and Collaboration
Overview
ZinkML provides robust collaboration features allowing teams to share and work together on Datasets, DataFlows, and Data Connectors. This documentation outlines the collaboration capabilities across different platform components.
Table of Contents
Dataset Collaboration
For a visual guide on Collaboration on Datasets, please watch our step-by-step tutorial:
Features
- Share datasets with team members
- Maintain dataset ownership
- Control access permissions
- Monitor usage
Capabilities
- Team members can:
- Analyze shared datasets
- Utilize data for their projects
- Create derivative works
Access Control
- Owner retains full control
- Access can be revoked at any time
- Usage tracking available
DataFlow Collaboration
For a visual guide on Collaboration on Dataflows, please watch our step-by-step tutorial:
Features
- Real-time collaboration
- Simultaneous editing
- Version control
- Change tracking
Capabilities
- Team members can:
- Co-edit dataflows
- Make simultaneous changes
- Test modifications
- Deploy versions
Access Management
- Owner maintains full control
- Revocable access
- Activity monitoring
- Permission settings
Data Connector Collaboration
For a visual guide on Collaboration on connectors, please watch our step-by-step tutorial:
Features
- Share connection configurations
- Maintain security
- Track usage
- Control access
Capabilities
- Team members can:
- Use shared connectors
- Pull data for projects
- Create data pipelines
- Import tables
Security Control
- Owner retains full rights
- Revocable permissions
- Usage analytics
- Access monitoring
Best Practices
General Guidelines
- Regular access review
- Clear documentation
- Communication protocols
- Version management
Security Recommendations
- Periodic permission audits
- Access level verification
- Usage monitoring
- Regular updates