# Connect Your Data Warehouse: Snowflake, BigQuery, Redshift and More

> Connect Snowflake, BigQuery, Redshift, Databricks, ClickHouse or MotherDuck so more of your team can explore the tables your data team maintains. Queries run in your warehouse, as the account you connect.

HTML version: https://supaboard.ai/product/data-warehouses

Bring your warehouse closer to your team.

Let finance, sales and operations ask about revenue, retention and performance in plain English, using the tables your data team already maintains.

## Connect directly

- [Snowflake](https://supaboard.ai/integrations/snowflake)
- [BigQuery](https://supaboard.ai/integrations/bigquery)
- Redshift
- [Databricks](https://supaboard.ai/integrations/databricks)
- ClickHouse
- MotherDuck

## Give business questions the right context.

Connect the tables your team already maintains, then add definitions such as what counts as revenue or an active account. Your existing pipelines continue to prepare the data.

**Existing tables, everyday questions** (illustrative table names)

- `finance.monthly_revenue` (month, revenue, accounts): "How did revenue change last quarter?"
- `product.account_retention` (cohort, started_accounts, active_at_3_months): "Which cohort kept the most accounts after three months?"

[Add knowledge and rules](https://supaboard.ai/product/knowledge-and-rules)

## Give your team a way into the warehouse.

1. **Connect an account.** Use the authentication method your warehouse supports, with the intended read access.
2. **Confirm the tables.** Choose the relevant project, dataset, database or schema and let Supaboard discover its structure.
3. **Set up the team’s agent.** An agent is the AI analyst set up for your team’s data. Give it the tables and business context it needs, and choose who can use it.

**Before you start:** Ask your data team for the right account, data scope and compute configuration. Setup fields differ by warehouse.

[Read the setup guide](https://docs.supaboard.ai/data-sources/connect-a-data-source)

## Queries run in your warehouse, using the account you connect.

Supaboard queries through the account you connect and uses your warehouse’s compute. Scope that account to the data you want to make available.

Answers reflect the latest data available in your warehouse tables.

**What a warehouse connection means**

- **Your warehouse compute.** Queries run there and can incur its usual usage costs.
- **The connected account’s permissions.** Access is limited to what that account can read.
- **Your tables’ freshness.** Answers reflect the data that has reached the warehouse.

## FAQ

### Does Supaboard replace our data pipelines?

No. Your pipelines continue to load and transform data into warehouse tables. Supaboard connects to those tables for analysis.

### Whose warehouse permissions do queries use?

Queries run using the account connected to Supaboard. They do not automatically use each teammate’s warehouse identity. Limit the connected account’s access, then configure data-source and agent access in Supaboard.

### Does Supaboard copy our warehouse?

Supaboard queries your connected warehouse without creating a full replica. Returned query results are saved with the conversation.

### Does querying incur warehouse costs?

Yes. Queries use your warehouse’s compute, so the warehouse’s usual usage charges can apply. Your data team should choose an appropriate compute setup.

### Can I compare warehouse data with an uploaded file?

Yes. For example, compare your revenue table with an uploaded forecast. Make sure the period and business definition match, and that the agent has access to the warehouse table.

## Related data sources

- [Connect an operational database](https://supaboard.ai/product/databases): Explore operational data with read-only queries, directly against your connected database.
- [Bring a file into the analysis](https://supaboard.ai/product/file-uploads): Turn an export, a spreadsheet or a document into something you can ask questions about.
- [All connection options](https://supaboard.ai/product/data-connections)

## Make your warehouse part of everyday work.

Connect the tables your team trusts. Start with their next question.

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