Visualization Skill

This skill creates charts and tables from metrics and attributes. It is used by other skills to display results and explore data visually.

How It Works

The Visualization skill creates and executes visualizations from your analytics data. When activated, the assistant:

1. Creates ad-hoc visualizations using metrics and dimensions
2. Validates visualization definitions before execution
3. Executes visualizations to retrieve data for analysis (when data sharing enabled)
4. Searches for attribute values across labels
5. Displays results as charts, tables, or other visual formats

The skill supports the following visualization types: TABLE, BAR, LINE, PIE, COLUMN, HEADLINE, and SCATTER. It can work with any metrics and attributes in your workspace. It’s used by other skills to display their results, making it a core dependency for most analytical capabilities.

Examples

Creating a Chart
The user asks: Show me revenue by region.
The AI Assistant then:

• selects the Revenue metric and the Region attribute,
• creates a bar chart, and
• displays the result.

Visualizing an Analysis Result
The user asks: Visualize the forecast for next quarter.
The AI Assistant then:

• takes the forecast output,
• creates a line chart to show the trend over time, and
• displays the result.

Exploring Data in a Table
The user asks: Create a table showing sales by product and month.
The AI Assistant then:

• selects the Sales metric and the Product and Month attributes,
• creates a table, and
• displays the result.

More Example Prompts

• Create a bar chart of sales by product.
• Show the clusters in a chart.
• Create a table of customer metrics.
• Show me a line chart over time.

Limitations

• Visualization creation requires appropriate workspace permissions
• Chart types depend on available metrics and dimensions
• Data sharing must be enabled for the AI Assistant to analyze visualization results and provide summaries (when disabled, visualizations are still created and displayed, but the assistant cannot access the data)
• Some complex visualizations may require specific metric/attribute combinations
• Attribute value search works across labels but may have limitations with very large attribute sets