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Analytics platforms

Lightdash (BI on dbt metrics)

Lightdash is an open-source business-intelligence tool that turns dbt models and their metric definitions into explorable dashboards, so metrics live in version-controlled code rather than the BI tool. This page describes its data model and privacy posture even-handedly, without ranking it against other BI tools.

Partially verified

What this means

Lightdash reads a dbt project and exposes its models, dimensions, and metric definitions as an explorable BI catalog, so the metrics in dashboards come from version-controlled dbt code rather than ad-hoc tool settings.

This keeps metric definitions reviewable and reusable, aligning the BI layer with the transformation layer.

Data model and posture

The model is dbt-centric: dimensions and metrics declared in dbt drive what Lightdash can explore, and queries run against the warehouse the dbt project targets.

Because it queries that warehouse, access is governed by warehouse grants, and the open-source nature lets teams self-host. Privacy posture depends on warehouse permissions and deployment choices rather than a vendor default.

How it appears in analytics and logs

Lightdash in a stack means dimensions and metrics defined in dbt drive the BI layer, so dashboard definitions are version-controlled and queries run in the warehouse dbt targets.

Diagnostic use case

Use Lightdash when you want BI dashboards defined from your dbt project, so metric logic stays in code review and the same definitions power exploration.

What WebmasterID can help detect

WebmasterID event data modeled in dbt can be surfaced in Lightdash; the BI layer is downstream of both collection and warehouse modeling.

Common mistakes

Privacy and accuracy notes

Lightdash queries the warehouse dbt builds on, so warehouse grants govern access to underlying data. This is educational, not legal advice.

Related pages

Sources and verification notes

Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.