Build dashboards with the copilot

Dashboards are a special, interactive artifact type. You give the copilot some data and describe what you want to see, and it builds the dashboard for you, no manual chart-building required. This guide covers providing data, creating a dashboard, refining it, and the limitations to keep in mind.

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Provide the data

A dashboard is built from data you give the copilot. You can provide it in three ways.

• Upload a file - CSV, Excel, PDF, and other common formats.
• Paste data - Paste it directly into the chat.
• Use a connected source - Where your workspace has one set up.

The copilot reads what you provide and works from that. If your file has multiple sheets or sections, tell the copilot which part matters.

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Create a dashboard

With data in hand, describe the outcome you want in plain language, not the chart mechanics. For example:

“Here’s our usage export. Build a dashboard showing adoption over time, the top Skills, and which teams are most active.”

The copilot then does the following.

1. Reads your data and identifies the relevant metrics.
2. Chooses appropriate visualizations, for example, line, bar, table, and KPI cards.
3. Lays them out into a single dashboard artifact in the side panel.

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Refine a dashboard

Iterate conversationally to shape the dashboard.

• Add or remove views - “Add a card for total active users.” / “Drop the geography map.”
• Change visualizations - “Make the usage trend a bar chart instead.”
• Filter and segment - “Break this down by team.” / “Only show the last 30 days.”
• Reorder layout - “Move the KPI cards to the top.”

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Good practices

A few habits produce a sharper dashboard.

• Give clean, well-labeled data. Clear column headers and consistent formatting help the copilot pick the right metrics and charts.
• Be specific about the question. “How is adoption trending?” produces a sharper dashboard than “show me some metrics.”
• Name your time window and segments. Specify the period, for example, “this quarter”, and how you want data sliced, for example, by team, by Skill, or by org.
• Download or link a snapshot when you need to share results, since a downloaded dashboard is a point-in-time snapshot rather than a live view.

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Limitations to keep in mind

Dashboards built this way are fast and conversational, with a few trade-offs.

• A dashboard reflects the data you provided when it was created. To update it, give the copilot fresh data, as it doesn’t refresh on its own.
• A shared or downloaded dashboard is a snapshot from when it was created, not a live, continuously updating view.
• Very large files or highly custom analytics may need a dedicated analytics tool. The copilot is built for fast, conversational dashboards rather than deep BI workflows.