Usage analytics project

The Lightdash analytics project brings your organization’s usage data into Lightdash. Start with the built-in dashboards, explore the underlying metrics, or save your own charts. You do not need to connect a warehouse or maintain a dbt project for it. This project is separate from the project-level User Activity dashboard. It covers captured activity across your organization, rather than one project’s fixed report. Use this page to create the project, update its content, choose a dashboard, or build your own analysis.

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Create your analytics project

1. Sign in with organization administration permissions.
2. Open Settings → Lightdash analytics.
3. Click Create. Lightdash creates the project and installs its built-in models, charts and dashboards.
4. Open a dashboard from the settings page, or click Explore to browse the available tables.

The project is restricted to organization administrators, even if someone has access to other projects. It can include user identities and usage from across the organization. Creating the project does not create historical events. Read Data freshness and history if a chart is empty after setup.

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Update models and dashboards

When Sync content is available in Settings → Lightdash analytics, click it to install the built-in content supplied by your instance’s release. Sync updates the models and built-in charts and dashboards in the existing project. You do not need to delete or recreate the project. Duplicate a built-in dashboard before customizing it. Sync replaces edits to built-in content; custom dashboards and separate copies are kept. Sync updates content definitions. It does not collect events, run the nightly data refresh, or add data from before capture was enabled.

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Built-in dashboards

Each dashboard groups related questions into tabs. The collection available to you depends on your deployed release and the content installed in your analytics project. Chart descriptions explain the measure and its limits. Open a chart’s Explore from here action to inspect its fields and filters before adapting it.

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Build your own analysis

Choose the Explore that matches what you want to count. An event, an app load, a person and an AI model call are different measures.

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Who uses which dashboards and apps?

Start with Adoption → People & content for dashboard audiences and Adoption → Data apps for app usage. For a custom dashboard-usage table, open Content reach. Select User name, Content name, Event ts → Day and Qualifying views, and filter Content type to dashboard. For app usage, open Data app reach. Select User name, App name, Event ts → Day, Total loads and Distinct viewers. Use View context to distinguish standalone apps, dashboards, charts and builder previews. To follow the Adoption dashboard’s app-usage scope, select standalone, dashboard and chart. These are separate Explores. Put their charts on the same dashboard to review them together; there is no combined dashboard-and-app viewer table in this collection. User activity can compare event categories by person and date, but does not supply the same per-content detail.

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How is Ask AI usage changing?

Start with Adoption → Ask AI, including Ask AI questions each day and People asking AI each week. To build the trend yourself, open Agent requests:

1. Filter Surface to web_app for Ask AI in the Lightdash web app.
2. Select Requested at → Day or Week.
3. Add Total requests and Distinct requesters.
4. Add Agent name or User name to compare agents or people.

Total requests includes captured follow-up prompts and requests that are pending or failed. Use request status to narrow the analysis. Other surfaces, such as Slack, are outside the web_app filter. Use AI usage for model calls and token consumption. Its ai.usage event represents a model call, not a question: one question can make several calls, and other AI features also make calls. Filter by Feature when comparing consumption. Tokens are not monetary cost or a complete measure of spending in external assistants.

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Data freshness and history

Usage data is collected after capture is enabled for your organization. The scheduled refresh processes closed UTC days at 00:30 UTC and updates the snapshots used for names and content inventory. Allow that job to finish before expecting the previous day’s data; these dashboards are not real-time monitors. Available history depends on when each event stream started capturing and how long its files are retained. Upgrading or syncing does not reconstruct earlier visits, missing identities or historical ownership. Names and inventory metadata can reflect the latest snapshot rather than the value at the event’s time. Keep these distinctions in mind when reading a chart:

• Views and loads are observed activity. Dashboard/chart views count qualifying backend fetches; app loads include reloads. They do not prove a person read the content or that an app rendered successfully.
• Distinct users are not additive. A person can appear on several days or use several items. Recalculate the distinct count for the whole period instead of adding daily or per-item counts.
• No observed use is not proof of safe deletion. Check the capture window and content dependencies before removing an item.
• Missing values are unknown. Historical errors, timings or identities may not have been captured; a blank value is not necessarily zero.

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Troubleshooting

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I cannot see Lightdash analytics in Settings

Check that your organization has access enabled and that your account has organization administration permissions. On a self-hosted instance, also check the deployment prerequisites.

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A dashboard is empty or missing fields

Check the selected dates, whether the relevant activity occurred after capture began, and whether the nightly refresh has completed. Use Sync content when it is offered to update the installed definitions. Sync does not force a data refresh. If a field remains missing after an instance upgrade, contact the Lightdash team.

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Who is “Unknown user”?

The event could not be matched to a name in the current user snapshot. It does not identify a particular type of actor. Use Explore from here and add User UUID alongside User name. A UUID distinguishes an identified actor whose name is unavailable from activity without a captured user UUID. Inspect Event name, View context, Source or Actor type where the Explore provides them. Do not assume every unknown user is an anonymous embed viewer or an AI agent. Keep UUIDs in the grouping when two people or content items share a name. You can hide the UUID column in the visualization while retaining separate groups.