/ga4-bigquery-schema

name: ga4-bigquery-schema
description: GA4 BigQuery Export Schema Reference — complete field reference, nested structures, query patterns, and performance tips
version: "1.0.0"
author: Cogny AI
platforms: []
user-invocable: true
argument-hint: "<query or topic>"
allowed-tools:
  - WebSearch
  - Read
  - Write
  - Bash

GA4 BigQuery Export Schema Reference

Complete reference guide to the Google Analytics 4 BigQuery export schema, including table structure, nested fields, common queries, and data processing best practices.

Full docs: https://cogny.com/docs/ga4-bigquery-export-schema

Usage

/ga4-bigquery-schema                      # Show full schema overview
/ga4-bigquery-schema event_params         # Explain event_params structure
/ga4-bigquery-schema conversion funnel    # Show conversion funnel query pattern
/ga4-bigquery-schema ecommerce            # Explain ecommerce fields

Instructions

You are a GA4 BigQuery schema expert. Use this reference to help users understand the GA4 export schema, write correct BigQuery SQL queries against GA4 data, and follow performance best practices.

When the user asks a question, find the relevant section below and provide precise, actionable answers with ready-to-use SQL examples.

If the user provides a specific topic as an argument, focus on that area. Otherwise, provide an overview of the schema structure.

---

Overview

Google Analytics 4 exports raw event data to BigQuery in a nested, denormalized format.

**Daily Tables:** `analytics_PROPERTY_ID.events_YYYYMMDD` **Intraday Tables:** `analytics_PROPERTY_ID.events_intraday_YYYYMMDD`

Each row represents a single event with nested fields for event parameters, user properties, and e-commerce data.

-- View table schema
SELECT
  column_name,
  data_type,
  description
FROM `project.analytics_123456789.INFORMATION_SCHEMA.COLUMNS`
WHERE table_name LIKE 'events_%'
ORDER BY ordinal_position

Top-Level Fields

| Field | Type | Description | |-------|------|-------------| | `event_date` | STRING | Date when the event was logged (YYYYMMDD format) | | `event_timestamp` | INTEGER | Time when the event was logged (microseconds since Unix epoch) | | `event_name` | STRING | Name of the event (e.g., 'page_view', 'purchase') | | `event_params` | ARRAY\<STRUCT\> | Array of event parameters | | `event_previous_timestamp` | INTEGER | Timestamp of previous event by this user | | `event_value_in_usd` | FLOAT | Value of the event in USD | | `event_bundle_sequence_id` | INTEGER | Sequential ID of the event bundle | | `event_server_timestamp_offset` | INTEGER | Timestamp offset between collection and server | | `user_id` | STRING | User ID set via setUserId API | | `user_pseudo_id` | STRING | Pseudonymous ID for the user (cookie-based) | | `user_properties` | ARRAY\<STRUCT\> | Array of user properties | | `user_first_touch_timestamp` | INTEGER | First time user visited (microseconds) | | `user_ltv` | STRUCT | User lifetime value information | | `device` | STRUCT | Device information | | `geo` | STRUCT | Geographic information | | `app_info` | STRUCT | App information (mobile apps) | | `traffic_source` | STRUCT | Traffic source information | | `stream_id` | STRING | Numeric ID of the data stream | | `platform` | STRING | Platform (web, ios, android) | | `ecommerce` | STRUCT | E-commerce transaction data | | `items` | ARRAY\<STRUCT\> | Array of item (product) details |

Nested Structures

event_params

Event parameters stored as key-value pairs:

STRUCT<
  key STRING,
  value STRUCT<
    string_value STRING,
    int_value INT64,
    float_value FLOAT64,
    double_value FLOAT64
  >
>

**Common event parameters:**

| Key | Type | Description | |-----|------|-------------| | `page_location` | string | Full URL of the page | | `page_title` | string | Title of the page | | `page_referrer` | string | Referrer URL | | `engagement_time_msec` | int | Engagement time in milliseconds | | `session_engaged` | int | Whether session was engaged (1/0) | | `ga_session_id` | int | Session ID | | `ga_session_number` | int | Session number for user |

**Example — extract event params:**

SELECT
  event_name,
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'page_location') as page_location,
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'page_title') as page_title,
  (SELECT value.int_value FROM UNNEST(event_params) WHERE key = 'engagement_time_msec') as engagement_time
FROM `project.analytics_123456789.events_*`
WHERE _TABLE_SUFFIX = FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
  AND event_name = 'page_view'
LIMIT 100

user_properties

User properties stored as key-value pairs:

STRUCT<
  key STRING,
  value STRUCT<
    string_value STRING,
    int_value INT64,
    float_value FLOAT64,
    double_value FLOAT64,
    set_timestamp_micros INT64
  >
>

**Example — extract user properties:**

SELECT
  user_pseudo_id,
  (SELECT value.string_value FROM UNNEST(user_properties) WHERE key = 'user_type') as user_type,
  (SELECT value.string_value FROM UNNEST(user_properties) WHERE key = 'plan_level') as plan_level
FROM `project.analytics_123456789.events_*`
WHERE _TABLE_SUFFIX = FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
GROUP BY user_pseudo_id, user_type, plan_level
LIMIT 100

device

STRUCT<
  category STRING,              -- desktop, mobile, tablet
  mobile_brand_name STRING,     -- Apple, Samsung, etc.
  mobile_model_name STRING,     -- iPhone 12, Galaxy S21, etc.
  mobile_marketing_name STRING,
  mobile_os_hardware_model STRING,
  operating_system STRING,      -- iOS, Android, Windows, macOS
  operating_system_version STRING,
  vendor_id STRING,
  advertising_id STRING,
  language STRING,              -- en-us, fr-fr, etc.
  is_limited_ad_tracking STRING,
  time_zone_offset_seconds INT64,
  browser STRING,               -- Chrome, Safari, Firefox
  browser_version STRING,
  web_info STRUCT<
    browser S