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Duration 14 hours
Course Outline
Introduction to WrenAI Spreadsheets and Metrics Library
- Overview of core capabilities and practical use cases
- Key distinctions compared to traditional spreadsheets
- Introduction to pre-built metric definitions
Getting Started with AI-Powered Spreadsheets
- Creating and formatting spreadsheet layouts
- Utilizing natural language for formulas and queries
- Leveraging AI assistance for data preparation
Working with the Metrics Library
- Exploring standardized KPIs across various departments
- Configuring metrics for RevOps, finance, and marketing teams
- Best practices for ensuring consistency and accuracy
Data Connectivity and Live Updates
- Linking spreadsheets to databases and SaaS platforms
- Automating data refresh cycles
- Managing permissions and access controls
Operational Reporting Workflows
- Developing recurring reports using templates
- Monitoring cross-functional performance indicators
- Setting up automated alerts and notifications
Visualization and Sharing
- Generating charts and dashboards from spreadsheet data
- Enabling real-time collaboration with team members
- Publishing reports for stakeholder review
Scaling Operational Analytics
- Applying the metrics library across multiple business units
- Standardizing reporting processes at an enterprise level
- Integrating with existing BI platforms
Advanced Features and Future Capabilities
- Exploring AI-driven forecasting within spreadsheets
- Customizing and expanding the metrics library
- Preview of upcoming features in WrenAI operational analytics
Summary and Next Steps
Requirements
- Basic knowledge of operational reporting principles
- Practical experience with spreadsheet applications
- Understanding of business metrics and KPIs
Target Audience
- Revenue operations (RevOps) teams
- Finance operations teams
- Marketing operations and PMO teams