Overview
This guide demonstrates how to build an analytics dashboard where users can interact with data through natural language. The AI generates appropriate visualizations and provides insights based on user queries.Architecture
An analytics dashboard with Tambo consists of:- Dashboard Layout - Grid or flex layout for organizing visualizations
- Graph Components - Charts registered with the AI for data visualization
- Data Context - Real-time data passed to the AI for analysis
- Chat Interface - Natural language queries for data exploration
- Control Panel - Filters and settings for data customization
Basic Dashboard Setup
Start with a simple dashboard layout:Adding Data Context
Provide real-time data context to help the AI generate accurate visualizations:Dashboard Layout with Charts
Create a responsive grid layout for visualizations:Interactive Chart Generation
Register multiple visualization types for different data scenarios:- Time Series
- Comparisons
- Distributions
Adding Filters and Controls
Implement dynamic filters that update the AI context:Real-time Data Updates
Update visualizations when data changes:Complete Dashboard Example
Here’s a production-ready analytics dashboard:Best Practices
Data Context
Data Context
- Keep context data concise and relevant
- Update context when filters change
- Include data summaries rather than raw datasets
- Format numbers for readability in context
Visualizations
Visualizations
- Provide clear component descriptions mentioning use cases
- Use appropriate chart types for different data patterns
- Include legends and labels for clarity
- Support responsive sizing for mobile devices
Performance
Performance
- Cache analytics data when possible
- Debounce filter changes to reduce API calls
- Use skeleton loaders during data fetching
- Implement virtual scrolling for large datasets
User Experience
User Experience
- Provide example queries to guide users
- Show loading states during data updates
- Validate date ranges and filter combinations
- Export visualizations as images or PDFs
Next Steps
- Explore the Analytics Template for a complete implementation
- Learn about Additional Context for passing dynamic data
- Add Local Tools for data fetching and calculations
- Implement User Authentication for personalized dashboards