> For the complete documentation index, see [llms.txt](https://docs.akkio.com/akkio-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.akkio.com/akkio-docs/integrations/google-bigquery-service-account.md). # Google BigQuery (Service Account) *BigQuery (Service User) support is currently **in beta**. Please raise any issues you encounter via the chat bubble in the bottom-right of the site, and we'll be happy to help.* *** ### Overview Our BigQuery integration allows you to import your data, allowing you to clean and transform your data as well as ask it questions via Chat Explore. This connection uses a Google Cloud *service account*. You will need access to IAM within your Google Cloud project. {% hint style="danger" %} You must allow network traffic from the public IP address `54.197.189.139` in order to allow Akkio to access your data. {% endhint %} ### Create a Service Account Click on this link to go to Google Cloud's service accounts page: If necessary, click on "CREATE SERVICE ACCOUNT" and set up a user.

You must assign a Role to the user that has at least the following IAM Permissions: **BigQuery Data Editor**, **BigQuery Job User, BigQuery Read Session User**\ \ You may use an existing role or create a new one. For documentation on how to create a Google IAM role, visit ### Download Service Account Token Click on this link to go to Google Cloud's service accounts page: Click the 3 dots next to your service account and select Manage keys

Click the Add Key button and select "Create new key"

Choose JSON. Clicking "Create" will download the JSON token

### Importing Data into Akkio To import data, first create a new project.

Select the Google BigQuery Service Account button.

Name your connection (like "My BigQuery Connection") and upload the JSON key you downloaded

Enter your BigQuery's dataset and table name information

Your data will begin to load

After a dataset is connected, the Flow will look the same as usual; you can merge with another dataset, modify using [Chat Data Prep](https://app.gitbook.com/o/-MUk5bRiktgkKBJI46_9/s/-MUiovvmaDi_ad2DYdZ4/building-a-model/selecting-model-data/chat-data-prep), or make a prediction. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.akkio.com/akkio-docs/integrations/google-bigquery-service-account.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.