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Duration 14 hours
Course Outline
Introduction to WrenAI Cloud
- Core features and system architecture
- Setting up accounts and preparing the environment
- Comparing WrenAI Cloud with traditional BI tools
Data Connectivity
- Linking to cloud-hosted databases
- Integrating spreadsheets and CSV files
- Overseeing and monitoring data connections
Data Modeling Fundamentals
- Defining datasets and schemas
- Creating relationships across data sources
- Best practices for designing models
Transformations and Enrichment
- Implementing filters and aggregations
- Utilizing calculated fields
- Automating data refresh cycles
Dashboard Design Principles
- Constructing interactive dashboards
- Selecting appropriate chart types and visualization best practices
- Optimizing layouts and user experience
Collaboration and Sharing
- Publishing dashboards for broader access
- Managing access controls and permissions
- Utilizing collaboration features within WrenAI Cloud
Administration and Monitoring
- Managing workspaces and project structures
- Monitoring performance metrics and usage
- Resolving common technical issues
Advanced Features and Roadmap
- Enhancing dashboards through integrations
- Discovering AI-assisted analytics capabilities
- Future developments in WrenAI Cloud
Summary and Next Steps
Requirements
- A foundational grasp of basic data analysis principles.
- Prior experience working with spreadsheets or entry-level BI tools.
- Comfort with using cloud-based applications.
Target Audience
- Data analysts
- BI developers
- Operations leads
