bigquery-basics
Manages datasets, tables, and jobs in BigQuery.
Skill by hermesonehq
Install
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
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.*
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Signals
- Stars
- 92
- Forks
- 19
- Open issues
- 1
- Last commit (this folder)
- Jun 28, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/hermesonehq/hermes-registry
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
bigquery-basics skill. Agent Mart. https://agentmart.dev/skills/hermesonehq-bigquery-basics (last updated 2026-10-24)