> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openlayer.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Connect a data source
> Learn how to connect your warehouse or lakehouse to Openlayer
To monitor data quality, Openlayer needs access to the **tables you want to track**.
You do this by connecting a data source (e.g., BigQuery, Snowflake, Databricks) and selecting the tables of interest.
Once connected, Openlayer will run automated tests directly on top of those tables.
## How to connect
**Prerequisites**:
* An [Openlayer project](/workspace-and-projects/creating-and-loading-projects) with monitoring mode enabled
* Appropriate credentials for your data source (see the provider-specific guides)
In your project, go to **Data sources** and click **Connect a data source**.
Select your provider:
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Each provider has its own authentication flow. For example, BigQuery supports both
**service account impersonation** and **service account key** uploads.
Follow the provider guide linked above for details.
You will be prompted for connection details, such as:
Openlayer stores these securely and uses them only to run queries on your behalf.
Once credentials are verified, you can browse the available databases/schemas and choose which tables to monitor.
For each table, you’ll also configure:
* A **timestamp column** (to order data in monitoring windows)
* An optional **data source name** (to label the connection in Openlayer)
After saving, Openlayer will profile the table and begin running data quality tests.
You can then add checks such as schema validation, drift detection, or anomaly detection.
See the [Tests overview](/tests/overview) for details on configuring tests.
## Next steps
* Connect your first source: [BigQuery guide](/integrations/bigquery)
* Learn how to [add data quality tests](/tests/overview)