bigquery-basics

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:

    gcloud services enable bigquery.googleapis.com --quiet

1. Create a Dataset:

    bq mk --dataset --location=US my_dataset

1. Create a Table:

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

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

Then create the table with the bq tool:

    bq mk --table my_dataset.mytable schema.json

1. Run a Query:

    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: Storage types, analytics

workflows, and BigQuery Studio features.

• CLI Usage: Essential bq command-line tool

operations for managing data and jobs.

• Client Libraries: Using Google Cloud

client libraries for Python, Java, Node.js, and Go.

• MCP Usage: Using the BigQuery remote MCP server and

Gemini CLI extension.

• Infrastructure as Code: Terraform examples for

datasets, tables, and reservations.

• IAM & Security: Roles, permissions, and data

governance best practices.

• AI Forecast: Leveraging pre-trained

TimesFM model for forecasting without custom training.

• AI Detect Anomalies: Identify

deviations in time series data using pre-trained TimesFM model.

• AI Generate: General-purpose text and

content generation using Gemini models.

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:

SKILL.md file for BigQuery AI and ML capabilities.

• BigQuery AI & ML References:

Reference files published for the BigQuery AI and ML skill.

• bigquery_ai_classify.md
• bigquery_ai_generate_bool.md
• bigquery_ai_generate_double.md
• bigquery_ai_generate_int.md
• bigquery_ai_if.md
• bigquery_ai_score.md
• bigquery_ai_search.md
• bigquery_ai_similarity.md