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Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use for SQL queries, resource management, data ingestion, or AI applications on BigQuery.

Use this Skill: https://skilld.dev/gh/davila7/claude-code-templates/bigquery-basics

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referencesiam-security.md

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BigQuery IAM & Security

BigQuery uses Identity and Access Management (IAM) to provide granular access control to its resources. As a security best practice, follow the principle of least privilege: grant only the permissions required to perform a specific action. This includes using the least permissive IAM role at the most granular level—such as the table or view level—that is necessary.

Predefined IAM Roles

For a complete list of predefined roles and detailed usage information, see BigQuery IAM roles.

Service Accounts and Agents

  • Default Service Account: BigQuery uses a managed service account (bq-PROJECT_NUMBER@bigquery-encryption.iam.gserviceaccount.com or the more general BigQuery Service Agent service-PROJECT_NUMBER@gcp-sa-bigquery.iam.gserviceaccount.com) for internal operations.

  • Service Account Impersonation: Use gcloud config set auth/impersonate_service_account for secure, temporary credential access.

Data Security

  • Encryption at Rest: All data is encrypted by default using Google-managed keys. Use Customer-Managed Encryption Keys (CMEK) for greater control.

  • VPC Service Controls: Define a service perimeter to prevent data exfiltration.

  • Column-Level Security: Use policy tags to restrict access to sensitive columns.

  • Row-Level Security: Use row access policies to filter data based on user identity.

  • Data Masking: Obscure sensitive data in a table while still permitting authorized users to access surrounding data.

  • Audit Logs: Record user activity and system events to enforce data governance policies and identify potential security risks.

  • Authorized Views: Allow users to query a view without granting them access to the underlying tables.

For more detailed information, see: BigQuery Security Overview.

Source: SKILL.md on GitHub

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    The skill provides comprehensive instructions for managing Google BigQuery resources using official tools and libraries. It includes references for CLI usage, client libraries, infrastructure as code, and security best practices. No malicious behaviors were identified.

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