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Duration 14 hours
Course Outline
Introduction to WrenAI Cloud
- Core features and system architecture
- Account initialization and environment setup
- Comparison between WrenAI Cloud and conventional BI tools
Data Connectivity
- Linking to cloud-based databases
- Incorporating spreadsheets and CSV files
- Oversight and monitoring of data connections
Foundations of Data Modeling
- Defining datasets and schemas
- Establishing links between different data sources
- Recommended practices for model architecture
Transformations and Enrichment
- Applying filters and aggregations
- Leveraging calculated fields
- Automating data refresh cycles
Principles of Dashboard Design
- Constructing interactive dashboards
- Chart selection and visualization best practices
- Optimizing layouts and user experience
Collaboration and Sharing
- Release management for dashboards
- Managing access control and permissions
- Utilizing collaboration tools within WrenAI Cloud
Administration and Monitoring
- Oversight of workspaces and projects
- Tracking performance and usage metrics
- Resolving common operational issues
Advanced Capabilities and Future Directions
- Expanding dashboard functionality via integrations
- Discovering AI-supported analytics
- Upcoming features and developments in WrenAI Cloud
Conclusion and Next Steps
Requirements
- Familiarity with fundamental data analysis principles
- Prior experience using spreadsheets or basic BI tools
- Knowledge of cloud-based application environments
Target Audience
- Data analysts
- BI developers
- Operations leads
