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bigquery-basics

Manages datasets, tables, and jobs in BigQuery.

Skill by hermesonehq

IndexedApache-2.0★ 92
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Manages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis.

Use cases: backend, data

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What's inside

Skill name
bigquery-basics
Description
Manages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis.
License
Apache-2.0
Metadata
category: BigDataAndAnalytics
Instructions
85 lines in SKILL.md · view on GitHub

Files (7)

  • SKILL.md
  • cli-usage.md · references/
  • client-library-usage.md · references/
  • core-concepts.md · references/
  • iac-usage.md · references/
  • iam-security.md · references/
  • mcp-usage.md · references/

SKILL.md (first lines)

# BigQuery Basics

BigQuery is a serverless, AI-ready data platform that enables high-speed
analysis of large datasets using SQL and Python. Its disaggregated architecture
separates compute and storage, allowing them to scale independently while
providing built-in machine learning, geospatial analysis, and business
intelligence capabilities.

## Setup and Basic Usage

1.  **Enable the BigQuery API:**

    ```bash
    gcloud services enable bigquery.googleapis.com --quiet
    ```

2.  **Create a Dataset:**

    ```bash
    bq mk --dataset --location=US my_dataset
    ```

3.  **Create a Table:**

    Create a file named `schema.json` with your table schema:

    ```json
    [
      {
        "name": "name",
        "type": "STRING",
        "mode": "REQUIRED"
      },
      {
        "name": "post_abbr",
        "type": "STRING",
        "mode": "NULLABLE"
      }
    ]
    ```

    Then create the table with the `bq` tool:

    ```bash
    bq mk --table my_dataset.mytable schema.json
    ```

4.  **Run a Query:**

    ```bash
    bq query --use_legacy_sql=false \
    'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` \
    WHERE state = "TX" LIMIT 10'
    ```

## Reference Directory

- [Core Concepts](references/core-concepts.md): Storage types, analytics
  workflows, and BigQuery Studio features.

- [CLI Usage](references/cli-usage.md): Essential `bq` command-line tool
  operations for managing data and jobs.

- [Client Libraries](references/client-library-usage.md): Using Google Cloud
  client libraries for Python, Java, Node.js, and Go.

- [MCP Usage](references/mcp-usage.md): Using the BigQuery remote MCP server and
  Gemini CLI extension.

- [Infrastructure as Code](references/iac-usage.md): Terraform examples for
  datasets, tables, and reservations.

- [IAM & Security](references/iam-security.md): Roles, permissions, and data
  governance best practices.

*If you need product information not found in these references, use the
Developer Knowledge MCP server `search_documents` tool.*

## Related Skills

- [BigQuery AI & ML Skill](../bigquery-ai-ml):
  SKILL.md file for BigQuery AI and ML capabilities (forecast, anomaly
  detection, text generation).

From hermesonehq/hermes-registry, Apache-2.0.

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Forks
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Last commit (this folder)
Jun 28, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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bigquery-basics skill. Agent Mart. https://agentmart.dev/skills/hermesonehq-bigquery-basics (last updated 2026-10-24)