# Google BigQuery

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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.

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This will trigger a dialog box to sign in with your Google account connected to your BigQuery instance.

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To use the integration, you'll need to give the required scopes. Read the information carefully before clicking allow.​

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Once your account is connected, you can select your project and bring in datasets.

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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.

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This contains a collection of tables (the datasets that the project will be able to interact with).

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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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# Agent Instructions: Querying This Documentation

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Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
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```

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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.