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Duration 14 hours
Course Outline
WrenAI Cloud Fundamentals
- Core features and system architecture.
- Account creation and environment setup.
- Comparing WrenAI Cloud with traditional BI tools.
Data Integration
- Connecting to cloud-based databases.
- Incorporating spreadsheets and CSV files.
- Oversight and monitoring of data connections.
Foundations of Data Modeling
- Defining datasets and schema structures.
- Establishing links between various data sources.
- Effective strategies for model design.
Data Transformation and Enrichment
- Implementing filters and aggregations.
- Leveraging calculated fields.
- Setting up automated data refreshes.
Principles of Dashboard Design
- Constructing interactive dashboard interfaces.
- Selecting chart types and visualization best practices.
- Optimizing layouts for enhanced user experience.
Collaboration and Distribution
- Deploying dashboards to stakeholders.
- Configuring access controls and permissions.
- Utilizing collaboration tools within WrenAI Cloud.
Administration and Oversight
- Managing workspaces and project structures.
- Tracking performance metrics and usage.
- Resolving common technical issues.
Advanced Capabilities and Future Directions
- Enhancing dashboards through integrations.
- Exploring AI-driven analytical features.
- Previewing upcoming developments in WrenAI Cloud.
Conclusion and Path Forward
Requirements
- Knowledge of fundamental data analysis principles.
- Proficiency with spreadsheets or entry-level BI tools.
- Basic understanding of cloud-based application environments.
Target Audience
- Data analysts.
- BI developers.
- Operations leaders.
