Charts & Data Visualization

Ask a question about your data and the AI doesn't just return a table — it renders an interactive chart right in the conversation. Hover for tooltips, click legend items to toggle series, and explore the visualization to fit your analysis workflow.

Understand the chart types available in Studio, how data flows from queries to visualizations, how to interact with rendered charts, and how to build multi-cell dashboards for comprehensive analysis.

• Signed in to Treasure AI Studio (Getting Started)
• Familiarity with the chat interface (AI Chat Interface)
• At least one database with queryable data in your Treasure AI account

Tables show you the numbers. Charts show you the story. When the AI returns query results alongside a chart, you can:

• Spot patterns instantly — Trend lines, outliers, and distributions are visible at a glance
• Validate AI reasoning — See whether the data supports the AI's summary or recommendation
• Iterate faster — Ask "now show this as a funnel" or "break it down by region" and get a new chart in seconds
• Share with stakeholders — Charts in dashboards communicate findings without requiring SQL literacy

The AI can generate a variety of chart types depending on your data and request. Common types include:

When you ask a question that benefits from visualization, the AI follows this sequence:

1. Query execution — The AI writes and runs a Trino query to retrieve data (see Query Execution)
2. Chart type selection — Based on the data shape and your request, the AI selects a chart type
3. Data mapping — The AI maps query columns to chart axes, series, and labels
4. File generation — The AI generates a self-contained HTML file with embedded chart logic and opens it in the file viewer

You see each step in the chat stream — the query as a tool call, then the chart rendering — so you can verify the data before trusting the visualization.

You: Show me daily signups for the last 30 days

AI: [Runs Trino query with td_interval(-30d)]
    [Renders line chart: x-axis = date, y-axis = signup count]

    Signups have been trending upward, with a notable spike on March 15
    that correlates with the product launch announcement.

Charts rendered as HTML support standard web interactions:

Charts appear in the file panel (right side of the screen). In the chat stream, you see a file notification card with the chart filename — click it to open the chart in the file viewer.

The AI typically applies a consistent color palette when generating charts, drawing from the Treasure AI design system. Colors may vary depending on the charting library the AI uses in the generated HTML.

The palette adapts to your theme:

• Light mode — Dark axis labels, light grid lines, light tooltip background
• Dark mode — Light axis labels, subtle grid lines, dark tooltip background

For comprehensive analysis, the AI will be able to build grid dashboards — multi-cell layouts combining charts, tables, KPIs, and other visualizations on a single page.

Ask the AI to build a dashboard by describing what you want to see:

You: Build a dashboard showing:
     - Total revenue and MoM growth as KPIs
     - Revenue by region as a bar chart
     - Daily revenue trend as a line chart
     - Top 10 customers as a table

The AI generates a multi-cell layout as an HTML file and displays the result in the file viewer. Each cell is independently scrollable and themed.

Dashboards will support multiple pages. A page selector dropdown at the top lets you switch between views — for example, "Overview," "Regional Breakdown," and "Customer Detail."

Understanding how the AI structures chart data helps you make more specific requests:

The AI maps your data to:

• Labels — Category or time axis (x-axis)
• Datasets — One or more data series, each with a label and values

Example: "Revenue and costs by quarter" produces:

• Labels: Q1, Q2, Q3, Q4
• Dataset 1: Revenue — [100, 150, 200, 250]
• Dataset 2: Costs — [60, 80, 90, 110]

Each slice or stage maps to:

• Name — Category label
• Value — Numeric amount

Each point maps to:

• X — Horizontal position
• Y — Vertical position
• Series — Group label (for multi-series scatter plots)

Flow data maps to:

• Nodes — Named entities (pages, stages, categories)
• Links — Connections between nodes with flow values

Hierarchical data maps to:

• Name — Category label
• Value — Area proportion

After reading this guide, you can:

• Request a chart from query results and understand how the AI selects the chart type
• Interact with a rendered chart using hover tooltips and legend toggles
• Request a specific chart type by name when the AI's default choice doesn't fit
• Ask the AI to build a multi-cell grid dashboard with mixed visualization types
• Explain the difference between a Sankey chart and a funnel chart

• Query Execution — Understand how queries feed data into charts
• Query Result Tables — Work with tabular data alongside charts
• File Output — Export charts and dashboards as files (PPTX, PDF)
• TDX Commands — Run CLI commands for data exploration before charting