Google BigQuery
Learn how to integrate AI agents with Google BigQuery using xpander.ai. Create intelligent workflows that automatically query, analyze, and act on large-scale datasets.
About Google BigQuery
Google BigQuery is a fully managed, serverless data warehouse and analytics platform offered by Google Cloud.
Key features include:
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Serverless Architecture: BigQuery eliminates the need for infrastructure management, allowing users to focus solely on data analysis.
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Scalability: It can process petabytes of data quickly, making it suitable for large-scale analytics.
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Built-in Machine Learning: With BigQuery ML, users can create and execute machine learning models directly within BigQuery using SQL, facilitating predictive analytics without extensive ML expertise.
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Real-time Analytics: BigQuery supports real-time data analysis, enabling timely insights for decision-making.
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Integration with Google Cloud Ecosystem: It seamlessly integrates with other Google Cloud services, such as Cloud Storage, Dataflow, and Looker Studio, enhancing data processing and visualization capabilities.
Authentication Options
Below are possible authentication options you can choose:
The simplest way to connect to Google BigQuery is by using xpander.ai’s built-in authentication:
- Go to the Apps section in the sidebar of your xpander.ai dashboard.
- Select BigQuery from the available integrations.
- Click Sign in with BigQuery.
- Grant xpander.ai permission to access your account.
- Your Google BigQuery integration is now ready to use.
The simplest way to connect to Google BigQuery is by using xpander.ai’s built-in authentication:
- Go to the Apps section in the sidebar of your xpander.ai dashboard.
- Select BigQuery from the available integrations.
- Click Sign in with BigQuery.
- Grant xpander.ai permission to access your account.
- Your Google BigQuery integration is now ready to use.
Generate a Google BigQuery API Token
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You’ll need access to the Google Cloud CLI tool to obtain your token. If it’s already installed, skip to step 5.
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Download the Google Cloud CLI tool.
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In the directory where you downloaded and extracted the SDK, run the installation script:
- After installation, add the SDK’s
bindirectory to your$PATH:
- Initialize the gcloud CLI:
- Run the following command and copy the token it generates:
Integrate Google BigQuery into xpander.ai
- Go to the Apps section in the sidebar of your xpander.ai dashboard.
- Select BigQuery from the available integrations.
- Click Other auth options.
- Enter an Interface name, e.g., “xpander-bigquery”.
- Select API Key as the authentication mode.
- Select Integration User as the authentication scope.
- Paste the Google BigQuery access token into the provided field.
- Choose Bearer as the Auth Type.
- Save the configuration.
Integration of Google BigQuery into AI Agent
Once you’ve configured your Google BigQuery account with the authentication option(s) described above, you can integrate it into your AI agent with xpander.ai:
- Go to the + sign located in the top right of the graph visualization of your xpander.ai agent.
- Select Apps.
- Choose BigQuery with the same Interface name you configured in the previous section (e.g., xpander-bigquery).
- Select the available Google BigQuery operations that suit your use case.
Expose Google BigQuery as MCP Server
Alternatively, you can also expose your Google BigQuery account as an MCP server. To do so:
- Go to the Apps section in the sidebar of your xpander.ai dashboard.
- Select BigQuery with the same Interface name you configured in the previous section (e.g., xpander-bigquery).
- Click MCP Configuration.
- Enter the MCP configuration into the appropriate settings of the client app you want to use (e.g., Cursor, Windsurf, Claude Desktop, etc.).
AI Agent Google BigQuery Prompt Library
Below are possible prompts or use cases you can try after integrating Google BigQuery into your xpander AI agent: