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What is BigQuery?

Google BigQuery is a fully-managed, serverless data warehouse that enables super-fast SQL queries using the processing power of Google’s infrastructure. It’s designed for analyzing large datasets and is commonly used for business intelligence, data analytics, and machine learning.

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BigQuery Connection Requirements

Unlike traditional databases that use username/password authentication, BigQuery uses Google Cloud Service Accounts for secure API access. This means you’ll need:

  1. A Google Cloud Project with BigQuery enabled
  2. A Service Account with appropriate permissions
  3. A Service Account Key (JSON file) for authentication

Service Account authentication is more secure than user credentials because it provides limited, role-based access and can be easily managed and rotated.

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Connecting Julius to BigQuery

Navigate to Data Connectors

  1. Go to your Julius Data Connectors Settings
  2. Click Create new Data Connector
  3. Select BigQuery from the available options

Configure Connection Details

You’ll see a form with the following fields:

Fields marked with an asterisk (*) are required to establish a connection.

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Connection Name*
string
  • What it is: A friendly name to identify this BigQuery connection
  • Example: “Production Analytics” or “Sales Data Warehouse”
  • Tip: Choose a name that helps you remember which BigQuery project/datasets this connects to
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SERVICE_ACCOUNT_JSON*
object
  • What it is: The complete JSON content from your downloaded service account key file
  • How to use: Open the downloaded JSON file in a text editor and copy the entire contents
  • Security: Julius encrypts and securely stores these credentials

Make sure to copy the entire JSON content including the opening and closing curly braces { }. Missing any part will cause authentication to fail.

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MFA_TYPE
string
  • What it is: Multi-Factor Authentication type if your organization requires additional security
  • When needed: Only if your Google Cloud organization has additional authentication requirements
  • Most users: Can leave this blank unless specifically required by your organization’s security policy

Test and Save Connection

  1. Click Add Connection to test the connection
  2. Julius will validate your service account credentials and access permissions
  3. If successful, your connector will be saved and ready to use
  4. If there’s an error, check the common issues section below

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Troubleshooting Common Issues

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Using Your BigQuery Connector

Once your BigQuery connector is set up:

  1. Start a conversation with Julius

  2. Ask about your data using natural language:

    • “Show me sales data from the last quarter”
    • “What’s the average order value by region?”
    • “Create a chart showing user growth over time”

  3. Julius will automatically:

    • Connect to your BigQuery project
    • Write and execute SQL queries
    • Handle BigQuery’s specific syntax and functions
    • Present results in easy-to-understand formats
    • Create visualizations when requested

Julius understands BigQuery’s unique features like nested/repeated fields, array functions, and standard SQL syntax. You don’t need to know BigQuery-specific SQL!