> 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.md).
# Google BigQuery
Google BigQuery integration is similar to GoogleSheets. To start, click “Create New Project” and select Google BigQuery as the primary input. This will take you to the Project Selection page, which will be empty. Select 'Connect Dataset' to begin connecting Google BigQuery.
This will trigger a dialog box to sign in with your Google account connected to your BigQuery instance.
To use the integration, you'll need to give the required scopes. Read the information carefully before clicking allow.
Once your account is connected, you can select your project and bring in datasets.
Due to the structure of Google BigQuery, there are a few layers to getting to what we would consider the dataset. With the project selected, you will select the BigQuery dataset.
This contains a collection of tables (the datasets that the project will be able to interact with).
After a dataset is connected, the project 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.
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