> For the complete documentation index, see [llms.txt](https://docs.alkemi.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.alkemi.ai/documentation/getting-started/connect-your-data/connecting-bigquery.md).

# Connecting BigQuery

{% stepper %}
{% step %}

### Click +Add under integrations

Click the **Add** button and select BigQuery.

<figure><img src="/files/y2TyONkxtnmQQP6gCZg9" alt=""><figcaption></figcaption></figure>

<figure><img src="/files/dlCDLgOa6yhdA2jL0oaB" alt=""><figcaption></figcaption></figure>
{% endstep %}

{% step %}

### Create a Google Cloud Service Account <a href="#input-a-connection-name-and-your-snowflake-account-id" id="input-a-connection-name-and-your-snowflake-account-id"></a>

Go to the IAM & Admin section of Google Cloud

<figure><img src="/files/Wl8t5P9cCACmteKw0DLx" alt="" width="563"><figcaption></figcaption></figure>

And go to the Service Users sub-section

<figure><img src="/files/eTlbLYfgX6ho8DIxbfCi" alt="" width="243"><figcaption></figcaption></figure>

Create a new Service Account

<figure><img src="/files/vVaaSCbr4y1S0rLuFcpC" alt="" width="563"><figcaption></figcaption></figure>

Add a name that will tell you later what it is and click "Done"

<figure><img src="/files/lnJ8lS1sHHrrl7V8TJqi" alt="" width="563"><figcaption></figcaption></figure>

Add Permissions

<figure><img src="/files/OlQsMdibXh8WZi9NhkzD" alt="" width="563"><figcaption></figcaption></figure>

And create and download a JSON key

<figure><img src="/files/EkqV3PX7sp0RVGmw1J1p" alt="" width="375"><figcaption></figcaption></figure>
{% endstep %}

{% step %}

### Gather BigQuery DataSet Information <a href="#input-a-connection-name-and-your-snowflake-account-id" id="input-a-connection-name-and-your-snowflake-account-id"></a>

Go to the BigQuery Console

<figure><img src="/files/9thU9J0Xcn12JfU6qpnk" alt="" width="375"><figcaption></figcaption></figure>

Select your DataSet and copy the ID of it

<figure><img src="/files/7qjcY0k6X0q9zFgfXZVs" alt="" width="375"><figcaption></figcaption></figure>

The ID is in the format of \[PROJECT\_ID].\[DATASET\_ID]
{% endstep %}

{% step %}

### Add Information to Alkemi <a href="#input-a-connection-name-and-your-snowflake-account-id" id="input-a-connection-name-and-your-snowflake-account-id"></a>

Use the first part of the DataSet ID, separated by a dot, as the Project ID. The second part is the Dataset ID. And copy in the contents of the JSON file for the secret key.

<figure><img src="/files/o7DdnCw9xHOlSQP6xYpW" alt="" width="375"><figcaption></figcaption></figure>
{% endstep %}

{% step %}

### Test and Save your connection <a href="#test-and-save-your-connection" id="test-and-save-your-connection"></a>

Click Test Connection and resolve any issues before clicking Save Connection
{% endstep %}

{% step %}

### Start creating data products! <a href="#start-creating-data-products" id="start-creating-data-products"></a>

Explore the creation of data products in DataLab for generating text-to-SQL queries on your BigQuery datasets. Enable MCP connections to integrate your data with chat clients like Claude, Cursor, and ChatGPT. For further information, refer to "Creating a Data Product.
{% endstep %}
{% endstepper %}

[<br>](https://open-2v.gitbook.com/url/preview/site_ybgqm/documentation/~/revisions/qNEJ8ULA5Br3aoLGqIDl/getting-started/connect-your-data/connecting-databricks)<br>


---

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