Claude can now turn a question about connected business data into a dashboard: it writes and runs SQL queries for the charts, then lets you inspect those queries and see when the data was last refreshed. The feature is in beta for paid Claude plans and is aimed at quick, exploratory questions—not replacing a dedicated analytics platform.
What Claude Dashboards does
Claude Dashboards connects to a data warehouse or another app connected to Claude, then builds visualizations from a natural-language request. Anthropic names Amazon Redshift, BigQuery, ClickHouse, Databricks, and Snowflake as examples of data warehouses, and Salesforce as an example of a connected app.
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For each chart, Claude generates a SQL query and runs it against the source. You can inspect the query behind a chart and check the dashboard’s data-refresh time. Those details make it possible to review what a chart is counting and whether its underlying data is current; they do not guarantee that the query or interpretation is correct.
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Who can use it and how to start
Dashboards is in beta on Claude Pro, Max, Team, and Enterprise plans, and it counts toward plan usage limits. Enterprise owners must enable it under Organization settings > Artifacts; Anthropic says Dashboards and Motion are off by default for Enterprise.
You can request a dashboard in a chat or choose a Dashboards template from the Artifacts tab. Dashboards start private to their creator, and users can share them. The exact data source options depend on which sources are connected and available to the account.
How to get a useful first dashboard
- Connect a source. Use a supported data warehouse or an app already connected to Claude. If you do not know whether a source is available to your account, check the connections offered in Claude.
- Ask a question, not just for a chart type. Specify the measure, time period, and breakdown you want. If you know the relevant table or app, name it.
- Refine the result conversationally. Ask Claude to adjust the dashboard if the groupings, dates, or presentation do not match the question.
- Inspect each chart’s query and refresh time. Check that the SQL reflects the intended measure and filters, and that the data timestamp suits the decision you need to make.
- Share only when ready. The dashboard is private to its creator initially; use the sharing option if others should see it.
Examples from Anthropic’s Help Center include “Build a dashboard of this quarter’s revenue by region,” “Show weekly signups for the last six months, split by plan,” and “Make a dashboard of my open Salesforce opportunities by stage and owner.” Its guidance is to describe what you want to know rather than only naming a visualization.
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When a dashboard is enough—and when it is not
Anthropic positions Dashboards for quick exploratory questions, such as comparing signups across weeks or months. It recommends moving to another analytics tool for deeper analysis. The announcement names Amplitude, Grafana, Hex, Mixpanel, Omni, Perplexity, PostHog, and Sigma as destinations, and lists Looker, monday.com, and Tableau as coming soon. These were the integrations and plans described in the announcement; they are not a guarantee of current availability for every account.
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| Consideration | Claude Dashboards | Established analytics workflow |
|---|---|---|
| Best fit | Quick, exploratory questions about connected data, as described by Anthropic. | Deeper analysis, for which Anthropic recommends continuing in another analytics tool. |
| Data access | Requires a connected warehouse or app that is available to the account. | Depends on the analytics platform and how the organization has configured it. |
| Query visibility | Each chart exposes its generated SQL query for inspection. | Varies by platform and workflow; no feature-by-feature comparison is provided in Anthropic’s materials. |
| Refresh visibility | The dashboard shows when its data was last refreshed. | Varies by platform; no comparative refresh details are provided. |
| Accuracy evidence | Anthropic’s documentation describes the workflow but does not establish an independent accuracy benchmark or performance guarantee. | No comparative accuracy benchmark is provided in the cited materials. |
The practical choice depends on whether the question is exploratory, whether the required source is connected, and whether your team needs the control and depth of its existing analytics process. Inspecting the SQL is particularly useful when a result looks surprising: a chart can be visually clear while still using the wrong date range, grouping, or definition of a metric.
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