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‎docs/integrations/data-visualization/lightdash-and-clickhouse.md‎

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import Image from '@theme/IdealImage';
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import PartnerBadge from '@theme/badges/PartnerBadge';
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# Goal
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# Lightdash
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In this guide, you’ll see how **Lightdash** connects to **ClickHouse** to explore your dbt models and build interactive dashboards.
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The example below shows a finished dashboard powered by data from ClickHouse.
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<PartnerBadge/>
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<Image size="lg" img={lightdash_02} alt="Lightdash dashboard example" border />
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Lightdash is the **AI-first BI platform** built for modern data teams, combining the openness of dbt with the performance of ClickHouse. By connecting ClickHouse to Lightdash, teams get an **AI-powered self-serve analytics experience** grounded in their dbt semantic layer, so every question is answered with governed, consistent metrics.
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# Connecting Lightdash to ClickHouse
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Developers love Lightdash for its open architecture, version-controlled YAML models, and integrations that fit directly into their workflow - from GitHub to the IDE.
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<PartnerBadge/>
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This partnership brings together **ClickHouse’s speed** and **Lightdash’s developer experience**, making it easier than ever to explore, visualize, and automate insights with AI.
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Lightdash is the **AI-first BI platform** built for modern data teams, combining the openness of dbt with the performance of ClickHouse. By connecting ClickHouse to Lightdash, teams get an **AI-powered self-serve analytics experience** grounded in their dbt semantic layer, so every question is answered with governed, consistent metrics.
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## Build an interactive dashboard with Lightdash and ClickHouse
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Developers love Lightdash for its open architecture, version-controlled YAML models, and integrations that fit directly into their workflow - from GitHub to the IDE.
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This partnership brings together **ClickHouse’s speed** and **Lightdash’s developer experience**, making it easier than ever to explore, visualize, and automate insights with AI.
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In this guide, you’ll see how **Lightdash** connects to **ClickHouse** to explore your dbt models and build interactive dashboards.
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The example below shows a finished dashboard powered by data from ClickHouse.
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<Image size="md" img={lightdash_02} alt="Lightdash dashboard example" border />
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<VerticalStepper headerLevel="h3">
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## Connection data required {#connection-data-required}
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### Gather connection data {#connection-data-required}
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When setting up your connection between Lightdash and ClickHouse, you’ll need the following details:
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---
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## Configuring your dbt profile for ClickHouse {#configuring-your-dbt-profile-for-clickhouse}
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### Configure your dbt profile for ClickHouse {#configuring-your-dbt-profile-for-clickhouse}
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In Lightdash, connections are based on your existing **dbt project**.
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To connect ClickHouse, make sure your local `~/.dbt/profiles.yml` file contains a valid ClickHouse target configuration.
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<Image size="md" img={lightdash_01} alt="Example profiles.yml configuration for a lightdash-clickhouse project" border />
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<br/>
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## Creating a Lightdash project connected to ClickHouse {#creating-a-lightdash-project-connected-to-clickhouse}
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### Create a Lightdash project connected to ClickHouse {#creating-a-lightdash-project-connected-to-clickhouse}
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Once your dbt profile is configured for ClickHouse, you’ll also need to connect your **dbt project** to Lightdash.
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Because this process is the same for all data warehouses, we won’t go into detail here — you can follow the official Lightdash guide for importing a dbt project:
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Because this process is the same for all data warehouses, we won’t go into detail here — you can follow the official Lightdash guide for importing a dbt project:
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[Import a dbt project → Lightdash Docs](https://docs.lightdash.com/get-started/setup-lightdash/connect-project#2-import-a-dbt-project?utm_source=clickhouse&utm_medium=partner&utm_campaign=integration_docs)
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After connecting your dbt project, Lightdash will automatically detect your ClickHouse configuration from the `profiles.yml` file. Once the connection test succeeds, you’ll be able to start exploring your dbt models and building dashboards powered by ClickHouse.
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## Exploring your ClickHouse data in Lightdash {#exploring-your-clickhouse-data-in-lightdash}
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### Explore your ClickHouse data in Lightdash {#exploring-your-clickhouse-data-in-lightdash}
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Once connected, Lightdash automatically syncs your dbt models and exposes:
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## Defining metrics and dimensions in Lightdash {#defining-metrics-and-dimensions-in-lightdash}
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### Define metrics and dimensions in Lightdash {#defining-metrics-and-dimensions-in-lightdash}
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In Lightdash, all **metrics** and **dimensions** are defined directly in your dbt model `.yml` files. This makes your business logic version-controlled, consistent, and fully transparent.
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Defining these in YAML ensures your team is using the same definitions across dashboards and analyses. For example, you can create reusable metrics like `total_order_count`, `total_revenue`, or `avg_order_value` right next to your dbt models — no duplication required in the UI.
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To learn more about how to define these, see the Lightdash guides:
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To learn more about how to define these, see the following Lightdash guides:
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- [How to create metrics](https://docs.lightdash.com/guides/how-to-create-metrics?utm_source=clickhouse&utm_medium=partner&utm_campaign=integration_docs)
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- [How to create dimensions](https://docs.lightdash.com/guides/how-to-create-dimensions?utm_source=clickhouse&utm_medium=partner&utm_campaign=integration_docs)
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---
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## Querying your data from tables {#querying-your-data-from-tables}
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### Query your data from tables {#querying-your-data-from-tables}
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Once your dbt project is connected and synced with Lightdash, you can start exploring data directly from your **tables** (or “explores”).
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Each table represents a dbt model and includes the metrics and dimensions you’ve defined in YAML.
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## Querying your data from tables {#querying-your-data-from-tables}
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Once your dbt project is connected and synced with Lightdash, you can start exploring data directly from your **tables** (also called “explores”).
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Each explore represents a dbt model and includes the metrics and dimensions you’ve defined in YAML.
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The **Explore** page is made up of five main areas:
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1. **Dimensions and Metrics** — all fields available on the selected table
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## Building dashboards {#building-dashboards}
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### Build dashboards {#building-dashboards}
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Once you’ve explored your data and saved visualizations, you can combine them into **dashboards** to share with your team.
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## Ask AI: self-serve analytics powered by dbt {#ask-ai}
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### Ask AI: self-serve analytics powered by dbt {#ask-ai}
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Lightdash’s **AI Agents** make data exploration truly self-serve.
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Instead of writing queries, users can simply ask questions in plain language — like *“What was our monthly revenue growth?”* — and the AI Agent automatically generates the right visualization, referencing your dbt-defined metrics and models to ensure accuracy and consistency.
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<Image size="lg" img={lightdash_06} alt="Lightdash Ask AI interface showing natural language query powered by dbt metrics" border />
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Learn more about AI Agents here:
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[AI Agents → Lightdash Docs](https://docs.lightdash.com/guides/ai-agents?utm_source=clickhouse&utm_medium=partner&utm_campaign=integration_docs)
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:::tip
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Learn more about AI Agents here: [AI Agents → Lightdash Docs](https://docs.lightdash.com/guides/ai-agents?utm_source=clickhouse&utm_medium=partner&utm_campaign=integration_docs)
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:::
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</VerticalStepper>
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## Learn more
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## Learn more {#learn-more}
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To learn more about connecting dbt projects to Lightdash, visit the [Lightdash Docs → ClickHouse setup](https://docs.lightdash.com/get-started/setup-lightdash/connect-project#clickhouse?utm_source=clickhouse&utm_medium=partner&utm_campaign=integration_docs).

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