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Duration 14 hours
Course Outline
Introduction to WrenAI Cloud
- Overview of core features and system architecture
- Setting up accounts and preparing the environment
- Comparing WrenAI Cloud with traditional BI tools
Data Connectivity
- Establishing connections to cloud-based databases
- Incorporating spreadsheets and CSV files
- Oversight and monitoring of data connections
Foundations of Data Modeling
- Defining datasets and schema structures
- Creating relationships across different data sources
- Best practices for designing data models
Data Transformation and Enrichment
- Implementing filters and aggregation methods
- Leveraging calculated fields
- Automating the process of data updates
Principles of Dashboard Design
- Constructing interactive dashboard interfaces
- Selecting chart types and applying visualization best practices
- Optimizing layout and user experience
Collaboration and Distribution
- Publishing dashboards for broader access
- Configuring access controls and permissions
- Utilizing collaboration tools within WrenAI Cloud
Administration and Performance Monitoring
- Overseeing workspaces and project management
- Tracking system performance and usage metrics
- Resolving common technical issues
Advanced Capabilities and Future Directions
- Enhancing dashboards through external integrations
- Discovering AI-driven analytics features
- Previewing upcoming functionalities in WrenAI Cloud
Conclusion and Recommended Next Steps
Requirements
- A solid grasp of fundamental data analysis concepts.
- Practical experience working with spreadsheets or basic BI tools.
- General familiarity with cloud-based software applications.
Intended Audience
- Data analysts.
- BI developers.
- Operations leads.
