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It combines **daily, fresh (360), and intraday exports** so the best available version of each event is always in use, adds session-level fields like `session_id` and `landing_page`, promotes key event parameters to columns, and fixes known GA4 export issues — handling the boilerplate transformations that are otherwise tedious to include in every GA4 query.\r\n\r\nThe goal of the package is to **speed up development** when building data models and pipelines on top of GA4 export data, allowing you to focus on your use case instead of wrestling with the raw export format.\r\n\r\n<img src=\"./docs/images/example_data_model.png\" alt=\"Example Data Model\" width=\"600\">\r\n\r\n*Example data model built with ga4-export-fixer*\r\n\r\n## Table of Contents\r\n<!-- TOC -->\n- [Blog Posts](#blog-posts)\n- [Main Features](#main-features)\n- [Planned Features](#planned-features)\n- [Installation](#installation)\n  - [Bash](#bash)\n  - [In Google Cloud Dataform](#in-google-cloud-dataform)\n- [Usage](#usage)\n  - [Create GA4 Events Enhanced Table](#create-ga4-events-enhanced-table)\n  - [Configuration Object](#configuration-object)\n  - [Assertions](#assertions)\n  - [Creating Incremental Downstream Tables from `ga4_events_enhanced`](#creating-incremental-downstream-tables-from-ga4_events_enhanced)\n  - [Helpers](#helpers)\n- [License](#license)\n<!-- /TOC -->\r\n\r\n## Blog Posts\r\n\r\n- [ga4-export-fixer: Getting started in Dataform](https://tanelytics.com/ga4-export-fixer-getting-started-in-dataform/)\r\n\r\n## Main Features\r\n\r\n<table>\r\n<tr>\r\n<td width=\"50%\" valign=\"top\">\r\n  <b>📦 Best Available Data</b><br>\r\n  Combines daily, fresh (360) &amp; intraday exports so the most complete version is always available\r\n</td>\r\n<td width=\"50%\" valign=\"top\">\r\n  <b>🔄 Incremental Updates</b><br>\r\n  Run on any schedule — daily, hourly, or custom\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>🧬 Data Enrichments</b><br>\r\n  Join external lookup data (cohorts, product master, etc.) at row level or ecommerce item level via <code>enrichments</code>\r\n</td>\r\n<td valign=\"top\">\r\n  <b>📐 Flexible Schema</b><br>\r\n  Keeps the flexible structure of the original export with key fields promoted to columns for better query performance; partitioning &amp; clustering enabled\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>🤖 AI Agent Ready</b><br>\r\n  Extensive table &amp; column descriptions for AI agents and humans\r\n</td>\r\n<td valign=\"top\">\r\n  <b>🔑 Session Identity Resolution</b><br>\r\n  <code>user_id</code> resolved per session; <code>merged_user_id</code> coalesces with <code>user_pseudo_id</code>\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>📡 Session Traffic Sources</b><br>\r\n  <code>session_first_traffic_source</code> and <code>session_traffic_source_last_click</code> computed automatically, adjusting for sessions that span midnight\r\n</td>\r\n<td valign=\"top\">\r\n  <b>📍 Landing Page Detection</b><br>\r\n  Derived per session from the first page where <code>entrances > 0</code>\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>🔗 Page URL Parsing</b><br>\r\n  Parsed <code>hostname</code>, <code>path</code>, <code>query</code>, and <code>query_params</code> from <code>page_location</code>\r\n</td>\r\n<td valign=\"top\">\r\n  <b>🛒 Ecommerce Data Fixes</b><br>\r\n  Nullifies placeholder <code>transaction_id</code>; corrects <code>purchase_revenue</code> bugs\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>🏷️ Item List Attribution</b><br>\r\n  Attributes <code>item_list_name</code>, <code>item_list_id</code>, and <code>item_list_index</code> from item selection events to downstream ecommerce events\r\n</td>\r\n<td valign=\"top\">\r\n  <b>⚙️ Event Parameter Handling</b><br>\r\n  Promote event params to columns; include or exclude by name\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>📊 Session Parameters</b><br>\r\n  Promote selected event parameters as <code>session_params</code>\r\n</td>\r\n<td valign=\"top\">\r\n  <b>⏱️ Custom Timestamp</b><br>\r\n  Use a custom event parameter as primary timestamp with automatic fallback\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>🔒 Schema Lock</b><br>\r\n  Lock table schema to a specific GA4 export date to prevent schema drift\r\n</td>\r\n<td valign=\"top\">\r\n  <b>✅ Data Freshness Tracking</b><br>\r\n  <code>data_is_final</code> flag and <code>export_type</code> label on every row\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>🔍 Data Quality Assertions</b><br>\r\n  Built-in daily assertion reconciles sessions, events, and revenue between the enhanced table and raw export\r\n</td>\r\n<td valign=\"top\">\r\n  <b>🔃 Selective Re-processing</b><br>\r\n  Re-process a date range without full table rebuild using <code>incrementalStartOverride</code> and <code>incrementalEndOverride</code>\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>📑 Batch Processing</b><br>\r\n  Process large exports in smaller batches via <code>numberOfDaysToProcess</code>\r\n</td>\r\n<td valign=\"top\">\r\n  <b>🕐 Timezone-Aware Datetime</b><br>\r\n  <code>event_datetime</code> converted to a configurable IANA timezone\r\n</td>\r\n</tr>\r\n<tr>\r\n<td valign=\"top\">\r\n  <b>🧩 Custom Processing Steps</b><br>\r\n  Append user-defined CTEs via <code>customSteps</code> to derive new columns or join external tables\r\n</td>\r\n<td valign=\"top\">\r\n  <b>🛡️ Zero Dependencies</b><br>\r\n  No additional external dependencies added to your Dataform repository\r\n</td>\r\n</tr>\r\n</table>\r\n\r\n## Planned Features\r\n\r\nFeatures under consideration for future releases:\r\n\r\n- Aggregated tables (ga4_session, ga4_ecommerce...)\r\n- Roll-ups for creating a single ga4_events_enhanced table from multiple source exports\r\n- Web and app specific default configurations\r\n- Custom channel grouping\r\n- Custom traffic source attribution\r\n\r\n## Installation\r\n\r\n### Bash\r\n\r\n```bash\r\nnpm install ga4-export-fixer\r\n```\r\n\r\n### In Google Cloud Dataform\r\n\r\nInclude the package in the package.json file in your Dataform repository.\r\n\r\n**`package.json`**\r\n\r\n```json\r\n{\r\n  \"dependencies\": {\r\n    \"@dataform/core\": \"3.0.42\",\r\n    \"ga4-export-fixer\": \"0.9.1\"\r\n  }\r\n}\r\n```\r\n\r\n**Note:** The best practice is to specify the package version explicitly (e.g. `\"0.1.2\"`) rather than using `\"latest\"` or `\"*\"`, to avoid unexpected breaking changes when the package is updated.\r\n\r\nIn Google Cloud Dataform, click \"Install Packages\" to install it in your development workspace.\r\n\r\nIf your Dataform repository does not have a package.json file, see this guide: [https://docs.cloud.google.com/dataform/docs/manage-repository#move-to-package-json](https://docs.cloud.google.com/dataform/docs/manage-repository#move-to-package-json)\r\n\r\n## Usage\r\n\r\n### Create GA4 Events Enhanced Table\r\n\r\nCreates an **enhanced** version of the GA4 BigQuery export (daily & intraday).\r\n\r\n#### JS Deployment (Recommended) ![.JS](https://img.shields.io/badge/.JS-F7DF1E?style=flat-square)\r\n\r\nCreate a new **ga4_events_enhanced** table using a **.js** file in your repository's **definitions** folder.\r\n\r\n**Using Defaults**\r\n\r\n**`definitions/ga4/ga4_events_enhanced.js`**\r\n\r\n```javascript\r\nconst { ga4EventsEnhanced } = require('ga4-export-fixer');\r\n\r\nconst config = {\r\n  // using hard-coded GA4 export path\r\n  sourceTable: '`project.analytics_12345.events_*`'\r\n};\r\n\r\nga4EventsEnhanced.createTable(publish, config);\r\n```\r\n\r\n**With Custom Configuration**\r\n\r\n**`definitions/ga4/ga4_events_enhanced.js`**\r\n\r\n```javascript\r\nconst { ga4EventsEnhanced } = require('ga4-export-fixer');\r\n\r\nconst config = {\r\n  // GA4 export path declared, using the table reference object\r\n  sourceTable: constants.GA4_TABLES.MY_GA4_EXPORT,\r\n  // use dataformTableConfig to make changes to the default Dataform table configuration\r\n  dataformTableConfig: {\r\n      schema: 'ga4'\r\n  },\r\n  // test configurations\r\n  test: false,\r\n  testConfig: {\r\n      dateRangeStart: 'current_date()-1',\r\n      dateRangeEnd: 'current_date()',\r\n  },\r\n  schemaLock: '20260101', // lock to daily export; also supports 'intraday_20260101' or 'fresh_20260101'\r\n  customTimestampParam: 'custom_event_timestamp', // custom timestamp collected as an event param\r\n  timezone: 'Europe/Helsinki',\r\n  // not needed data\r\n  excludedColumns: [\r\n    'app_info',\r\n    'publisher'\r\n  ],\r\n  // not needed events\r\n  excludedEvents: [\r\n    'session_start',\r\n    'first_visit',\r\n    'user_engagement'\r\n  ],\r\n  // transform to session-level\r\n  sessionParams: [\r\n    'user_agent'\r\n  ],\r\n  // promote as columns\r\n  eventParamsToColumns: [\r\n    {name: 'session_engaged'},\r\n    {name: 'ga_session_number', type: 'int'},\r\n    {name: 'page_type', type: 'string'},\r\n  ],\r\n  // not needed in the event_params array\r\n  excludedEventParams: [\r\n    'session_engaged',\r\n    'ga_session_number',\r\n    'page_type',\r\n    'user_agent'\r\n  ],\r\n  // use export type for data_is_final instead of the default DAY_THRESHOLD\r\n  dataIsFinal: {\r\n    detectionMethod: 'EXPORT_TYPE',\r\n  },\r\n  // attribute item lists to downstream ecommerce events within the same session\r\n  itemListAttribution: {\r\n    lookbackType: 'SESSION',\r\n  },\r\n};\r\n\r\nga4EventsEnhanced.createTable(publish, config);\r\n```\r\n\r\n#### SQLX Deployment ![.SQLX](https://img.shields.io/badge/.SQLX-4285F4?style=flat-square)\r\n\r\nAlternatively, you can create the **ga4_events_enhanced** table using a .SQLX file.\r\n\r\n**`definitions/ga4/ga4_events_enhanced.sqlx`**\r\n\r\n```javascript\r\nconfig {\r\n  type: \"incremental\",\r\n  description: \"GA4 Events Enhanced table\",\r\n  schema: \"ga4\",\r\n  onSchemaChange: \"EXTEND\",\r\n  bigquery: {\r\n    partitionBy: \"event_date\",\r\n    clusterBy: ['event_name', 'session_id', 'page_location', 'data_is_final'],\r\n  },\r\n  tags: ['ga4_export_fixer']\r\n}\r\n\r\njs {\r\n  const { ga4EventsEnhanced } = require('ga4-export-fixer');\r\n\r\n  const config = {\r\n    // using hard-coded GA4 export path\r\n    sourceTable: '`project.analytics_12345.events_*`',\r\n    self: self(),\r\n    incremental: incremental()\r\n  };\r\n}\r\n\r\n${ga4EventsEnhanced.generateSql(config)}\r\n\r\npre_operations {\r\n  ${ga4EventsEnhanced.setPreOperations(config)}\r\n}\r\n```\r\n\r\n<br>\r\n\r\n---\r\n\r\n### Configuration Object\r\n\r\nAll fields are optional except `sourceTable`. Default values are applied automatically, so you only need to specify the fields you want to override.\r\n\r\n\r\n| Field                  | Type                    | Default/Required                   | Description                                                                                                                                                                                                                                                                                                                  |\r\n| ---------------------- | ----------------------- | ---------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `sourceTable`          | Dataform ref / object / string | **required**                       | Source GA4 export table. Inside an SQLX `js { }` block use `ref(...)`. From a `.js` definition file use a `{ schema, name }` ref object (resolved later via `ctx.ref()`) or a backtick-quoted ``` `project.dataset.events_*` ``` string for an external table. |\r\n| `self`                 | Dataform self()         | **required for .SQLX deployment**  | Reference to the table itself. Use `self()` in Dataform                                                                                                                                                                                                                                                                      |\r\n| `incremental`          | Dataform incremental()  | **required for .SQLX deployment**  | Switch between incremental and full refresh logic. Use `incremental()` in Dataform                                                                                                                                                                                                                                           |\r\n| `dataformTableConfig`  | object                  | **In JS deployment only.** [See default](#default-dataformtableconfig) | Override the default Dataform table configuration for JS deployment. See: [ITableConfig reference](https://docs.cloud.google.com/dataform/docs/reference/dataform-core-reference#itableconfig) |\r\n| `schemaLock`           | string                  | `undefined`                        | Lock the table schema to a specific GA4 export table suffix. Accepts `\"YYYYMMDD\"` (daily), `\"intraday_YYYYMMDD\"`, or `\"fresh_YYYYMMDD\"`. Date must be >= `\"20241009\"`                                                                                                                                                        |\r\n| `timezone`             | string                  | `'Etc/UTC'`                        | IANA timezone for event datetime (e.g. `'Europe/Helsinki'`)                                                                                                                                                                                                                                                                  |\r\n| `customTimestampParam` | string                  | `undefined`                        | Name of a custom event parameter containing a JS timestamp in milliseconds (e.g. collected via `Date.now()`)                                                                                                                                                                                                                 |\r\n| `bufferDays`           | integer                 | `1`                                | Extra days to include for sessions that span midnight. Auto-adjusted when `itemListAttribution.lookbackType` is `'TIME'` and the lookback exceeds `bufferDays`                                                                                                                                                               |\r\n| `itemListAttribution`  | object                  | `undefined`                        | Enable item list attribution. See [Item List Attribution](#item-list-attribution)                                                                                                                                                                                                                                            |\r\n| `test`                 | boolean                 | `false`                            | Enable test mode (uses `testConfig` date range instead of pre-operations)                                                                                                                                                                                                                                                    |\r\n| `excludedEventParams`  | string[]                | `[]`                               | Event parameter names to exclude from the `event_params` array                                                                                                                                                                                                                                                               |\r\n| `excludedEvents`       | string[]                | `['session_start', 'first_visit']` | Event names to exclude from the table. These events are excluded by default because they have no use for analysis purposes. Override this to include them if needed                                                                                                                                                          |\r\n| `excludedColumns`      | string[]                | `[]`                               | Default GA4 export columns to exclude from the final table, for example `'app_info'` or `'publisher'`                                                                                                                                                                                                                        |\r\n| `sessionParams`        | string[]                | `[]`                               | Event parameter names to aggregate as session-level parameters                                                                                                                                                                                                                                                               |\r\n| `includedExportTypes`  | object                  | [See details](#includedExportTypes) | Which GA4 export types to include (daily, fresh, intraday)                                                                                                                                                                                                                                                                  |\r\n| `dataIsFinal`          | object                  | [See details](#dataIsFinal)         | How to determine whether data is final (not expected to change)                                                                                                                                                                                                                                                              |\r\n| `testConfig`           | object                  | [See details](#testConfig)          | Date range used when `test` is `true`                                                                                                                                                                                                                                                                                        |\r\n| `preOperations`        | object                  | [See details](#preOperations)       | Date range and incremental refresh configuration                                                                                                                                                                                                                                                                             |\r\n| `eventParamsToColumns` | object[]                | `[]`                                | Event parameters to promote to columns. [See item schema](#eventParamsToColumns)                                                                                                                                                                                                                                             |\r\n| `customSteps`          | object[]                | `[]`                                | User-defined CTEs appended to the pipeline after `enhanced_events`. [See Custom CTEs](#custom-ctes)                                                                                                                                                                                                                          |\r\n| `enrichments`          | object[]                | `[]`                                | Declarative external-data enrichments joined into `enhanced_events`. [See Data Enrichments](#data-enrichments)                                                                                                                                                                                                               |\r\n\r\n<a id=\"default-dataformtableconfig\"></a>\r\n<details>\r\n<summary><strong>Default dataformTableConfig</strong></summary>\r\n\r\n```json\r\n{\r\n    \"name\": \"ga4_events_enhanced_<dataset_id>\",\r\n    \"type\": \"incremental\",\r\n    \"schema\": \"<source_dataset>\",\r\n    \"description\": \"<default description>\",\r\n    \"bigquery\": {\r\n        \"partitionBy\": \"event_date\",\r\n        \"clusterBy\": [\r\n            \"event_name\",\r\n            \"session_id\",\r\n            \"page_location\",\r\n            \"data_is_final\"\r\n        ],\r\n        \"labels\": {\r\n            \"ga4_export_fixer\": \"true\"\r\n        }\r\n    },\r\n    \"onSchemaChange\": \"EXTEND\",\r\n    \"tags\": [\r\n        \"ga4_export_fixer\"\r\n    ]\r\n}\r\n```\r\n\r\nThe `onSchemaChange: \"EXTEND\"` setting updates the result table schema on incremental runs, adding columns for any new fields the query produces.\r\n\r\n</details>\r\n<br>\r\n\r\n<a id=\"includedExportTypes\"></a>\r\n\r\n**`includedExportTypes`** — which GA4 export types to include:\r\n\r\n\r\n| Field                          | Type    | Default | Description                      |\r\n| ------------------------------ | ------- | ------- | -------------------------------- |\r\n| `includedExportTypes.daily`    | boolean | `true`  | Include daily (processed) export |\r\n| `includedExportTypes.fresh`    | boolean | `false` | Include fresh (hourly-updated) export |\r\n| `includedExportTypes.intraday` | boolean | `true`  | Include intraday export          |\r\n\r\n\r\nExport priority: **daily > fresh > intraday**. Each lower-priority export only provides data not already covered by a higher-priority one. All seven combinations of the three export types are supported.\r\n\r\nWhen all three exports are enabled, the package:\r\n1. Gets all data from daily export tables\r\n2. Gets fresh export data for days not yet covered by a daily table\r\n3. Gets intraday export data for events after the latest fresh event timestamp\r\n\r\nThe boundary between fresh and intraday is timestamp-based because the fresh export is updated hourly, so within the same day some events come from the fresh export and the rest from intraday.\r\n\r\n> **Without daily export:** When `daily` is `false`, `dataIsFinal.detectionMethod` must be set to `'DAY_THRESHOLD'`, because `EXPORT_TYPE` detection relies on daily tables to mark data as final.\r\n\r\n<a id=\"dataIsFinal\"></a>\r\n\r\n**`dataIsFinal`** — how to determine whether data is final (not expected to change):\r\n\r\n\r\n| Field                         | Type    | Default         | Description                                                                                                                                                                                     |\r\n| ----------------------------- | ------- | --------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `dataIsFinal.detectionMethod` | string  | `'DAY_THRESHOLD'` | `'DAY_THRESHOLD'` (uses days since event; data older than `dayThreshold` is considered final) or `'EXPORT_TYPE'` (uses table suffix; all data from the daily export is considered final). `'EXPORT_TYPE'` is suitable for most **web only** properties as data is rarely received with a delay. Must be `'DAY_THRESHOLD'` when daily export is not enabled |\r\n| `dataIsFinal.dayThreshold`    | integer | `3`               | Days after which data is considered final. According to GA4 documentation, data up to 72 hours old is subject to possible changes. Required when `detectionMethod` is `'DAY_THRESHOLD'`            |\r\n\r\n\r\n<a id=\"testConfig\"></a>\r\n\r\n**`testConfig`** — date range used when `test` is `true`:\r\n\r\n\r\n| Field                       | Type              | Default              | Description                 |\r\n| --------------------------- | ----------------- | -------------------- | --------------------------- |\r\n| `testConfig.dateRangeStart` | string (SQL date) | `'current_date()-1'` | Start date for test queries |\r\n| `testConfig.dateRangeEnd`   | string (SQL date) | `'current_date()'`   | End date for test queries   |\r\n\r\n\r\n<a id=\"preOperations\"></a>\r\n\r\n**`preOperations`** — date range and incremental refresh configuration:\r\n\r\n\r\n| Field                                      | Type              | Default              | Description                                                                                                                                                                                         |\r\n| ------------------------------------------ | ----------------- | -------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `preOperations.dateRangeStartFullRefresh`  | string (SQL date) | `'date(2000, 1, 1)'` | Start date for full refresh                                                                                                                                                                         |\r\n| `preOperations.dateRangeEnd`               | string (SQL date) | `'current_date()'`   | End date for queries                                                                                                                                                                                |\r\n| `preOperations.numberOfPreviousDaysToScan` | integer           | `10`                 | Number of days to scan backwards from the result table's last partition when determining the incremental refresh start checkpoint. Needs to cover the number of days that can still contain not final `(data_is_final = false)` data                                                                    |\r\n| `preOperations.incrementalStartOverride`   | string (SQL date) | `undefined`          | Override the incremental start date to re-process a specific range                                                                                                                                  |\r\n| `preOperations.incrementalEndOverride`     | string (SQL date) | `undefined`          | Override the incremental end date to re-process a specific range                                                                                                                                    |\r\n| `preOperations.numberOfDaysToProcess`      | integer           | `undefined`          | Limit each run to N days of data. When set, the end date becomes `start + N - 1` (capped at `current_date()`). When `undefined`, `dateRangeEnd` is used as-is. `incrementalEndOverride` takes priority  |\r\n\r\nDate fields (`dateRangeStart`, `dateRangeEnd`, etc.) accept string dates in `YYYYMMDD` or `YYYY-MM-DD` format, or BigQuery SQL expressions (e.g. `'current_date()'`, `'date(2026, 1, 1)'`).\r\n\r\n<a id=\"eventParamsToColumns\"></a>\r\n\r\n**`eventParamsToColumns`** — each item in the array is an object:\r\n\r\n\r\n| Field        | Type   | Required | Description                                                                                                                           |\r\n| ------------ | ------ | -------- | ------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `name`       | string | Yes      | Event parameter name                                                                                                                  |\r\n| `type`       | string | No       | Data type: `'string'`, `'int'`, `'int64'`, `'double'`, `'float'`, or `'float64'`. If omitted, returns the value converted to a string |\r\n| `columnName` | string | No       | Column name in the output. Defaults to the parameter `name`                                                                           |\r\n\r\n\r\n<a id=\"item-list-attribution\"></a>\r\n\r\n**`itemListAttribution`** — when set to an object, enables attribution of `item_list_name`, `item_list_id`, and `item_list_index` from `select_item`/`select_promotion` events to downstream ecommerce events (e.g. `add_to_cart`, `purchase`). Disabled by default.\r\n\r\n| Field            | Type    | Required                    | Description                                                           |\r\n| ---------------- | ------- | --------------------------- | --------------------------------------------------------------------- |\r\n| `lookbackType`   | string  | Yes                         | `'SESSION'` (partition by session) or `'TIME'` (time-based window)    |\r\n| `lookbackTimeMs` | integer | When `lookbackType: 'TIME'` | Lookback window in milliseconds (e.g. `86400000` for 24h)            |\r\n\r\n```javascript\r\n// Session-based: attribute within the same session\r\nitemListAttribution: { lookbackType: 'SESSION' }\r\n\r\n// Time-based: attribute within a 24-hour window across sessions\r\nitemListAttribution: { lookbackType: 'TIME', lookbackTimeMs: 86400000 }\r\n```\r\n\r\n> **Note:** This feature adds a compute-heavy CTE with a window function over unnested items. Only enable it if you need item list attribution for ecommerce analysis.\r\n\r\n<a id=\"custom-ctes\"></a>\r\n\r\n**`customSteps`** — append CTEs after `enhanced_events`. Each entry is either a raw `{name, query}` or a structured `{name, select, from, ...}`. The last entry becomes the table's final SELECT; earlier entries become CTEs.\r\n\r\n**Stable CTE names you can reference from your custom steps:**\r\n\r\n| Name                     | Always present?                       | Contents                                                                                                                                            |\r\n| ------------------------ | ------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `event_data`             | yes                                   | Extracted and shaped events from `sourceTable`, with date filtering and column promotions applied. *Unfiltered for the buffer-days range.*           |\r\n| `session_data`           | yes                                   | Session-level aggregations (grouped by `session_id`).                                                                                                |\r\n| `items_unnested`         | only when `itemListAttribution` is on | Per-event item rows (one row per item per ecommerce event), with attribution window function applied.                                                |\r\n| `items_rebuilt`          | only when `itemListAttribution` is on | Re-aggregated items with attributed list fields, joined back to events via `_item_row_id`.                                                           |\r\n| `enrich_<name>`          | only when configured via `enrichments` | One CTE per [enrichment](#data-enrichments) entry, providing dim data for joining into `enhanced_events`.                                              |\r\n| `enhanced_events`        | yes                                   | The package's standard output shape (joined event_data + session_data + items_rebuilt + enrich_*, columns ordered, incremental date filter applied). The natural starting point for most custom CTEs. |\r\n\r\nExample custom step using the raw SQL format:\r\n\r\n```javascript\r\n// Add a content_group column derived from page.path\r\ncustomSteps: [\r\n    {\r\n        name: 'final',\r\n        query: `select\r\n  enhanced_events.*,\r\n  case\r\n    when page.path like '/blog/%' then 'blog'\r\n    when page.path like '/products/%' then 'product'\r\n    when page.path = '/' then 'home'\r\n    else 'other'\r\n  end as content_group\r\nfrom enhanced_events`,\r\n    },\r\n],\r\n```\r\n\r\nThe same example in the structured shape:\r\n\r\n```javascript\r\ncustomSteps: [\r\n    {\r\n        name: 'final',\r\n        select: {\r\n            columns: {\r\n                '[sql]passthrough': 'enhanced_events.*',\r\n                content_group: `case\r\n  when page.path like '/blog/%' then 'blog'\r\n  when page.path like '/products/%' then 'product'\r\n  when page.path = '/' then 'home'\r\n  else 'other'\r\nend`,\r\n            },\r\n        },\r\n        from: 'enhanced_events',\r\n    },\r\n],\r\n```\r\n\r\n> **Note:** Custom columns aren't auto-documented. Use `dataformTableConfig.columns` to add descriptions — it's deep-merged with the package's defaults, so your keys are added or override matching defaults, and untouched defaults stay.\r\n\r\n> **Note:** Built-in assertions assume the package's standard schema. If your custom CTEs rename, drop, or filter rows in ways that break those assumptions, disable the affected assertions explicitly via the `assertions` config option.\r\n\r\n<a id=\"data-enrichments\"></a>\r\n\r\n**`enrichments`** — declaratively join external dimension data into `enhanced_events` (cohort labels, page metadata, marketing attribution, etc.). Each entry describes one dim source plus the join — the package generates the source CTE, the `LEFT JOIN`, and column descriptions automatically.\r\n\r\nFor typical use cases this is the right tool; reach for `customSteps` only when you need a transformation that doesn't fit a flat dim join.\r\n\r\n**Per-enrichment shape:**\r\n\r\n| Field | Type | Required | Description |\r\n| --- | --- | --- | --- |\r\n| `name` | string | Yes | Used in the generated `enrich_<name>` CTE name. Unique within `enrichments`. |\r\n| `level` | `'row'` / `'item'` | No, defaults to `'row'` | Join grain. `'row'` joins external dim data onto each row of `enhanced_events` (any column on `enhanced_events` as the key). `'item'` joins external dim data onto each item inside the `items` array (any field on the items struct or any event_data column as the key). |\r\n| `source` | Dataform ref / object / string | Yes | Source dim table. Inside an SQLX `js { }` block use `ref(...)`. From a `.js` definition file use a `{ schema, name }` ref object (resolved later via `ctx.ref()`) or a backtick-quoted ``` `project.dataset.table` ``` string for an external table. |\r\n| `joinKey` | string / string[] | Yes | For `level: 'row'`: column name(s) on `enhanced_events`. For `level: 'item'`: field name(s) on the items struct (e.g. `'item_id'`) or column name(s) on `event_data` (e.g. `'user_pseudo_id'`). Composite keys (array) compile to `USING(col1, col2, ...)`. |\r\n| `columns` | string[] | Yes | Source columns to add to the output (excluding `joinKey`). Names matching existing columns are coalesced with the original (`coalesce(enrich.col, original)`) so missed JOINs fall back to the existing value. |\r\n| `dedupe` | boolean | No, defaults to `false` | When `true`, wraps the source CTE in `qualify row_number() over (partition by <joinKey>) = 1` for non-unique-key dim sources. Non-deterministic which row wins; for strict needs, pre-aggregate in source SQL. |\r\n\r\n**Coalesce-or-add semantics.** If an enrichment column name matches an existing column on `enhanced_events` (a column promoted via `eventParamsToColumns`, a package-generated column, or a default GA4 column from the export), the enrichment value is coalesced with the original: `coalesce(enrich_<name>.<col>, <original>) as <col>`. Rows where the JOIN matches get the enrichment value; rows where it misses fall back to the existing value rather than going NULL. If there is no overlap, the column is added as a plain `enrich_<name>.<col>`.\r\n\r\n**Example** — attach user cohort labels by `user_pseudo_id` (Dataform-declared table referenced by `{ schema, name }`):\r\n\r\n```javascript\r\nenrichments: [\r\n    {\r\n        name: 'cohorts',\r\n        // level omitted → defaults to 'row'\r\n        source: { schema: 'analytics', name: 'user_cohorts' },\r\n        joinKey: 'user_pseudo_id',\r\n        columns: ['cohort_label', 'lifecycle_stage'],\r\n    },\r\n],\r\n```\r\n\r\n**Example** — composite key (date + user) for daily-varying dim data, with dedupe safety net (external table referenced by backtick-FQN):\r\n\r\n```javascript\r\nenrichments: [\r\n    {\r\n        name: 'segments',\r\n        level: 'row',\r\n        source: '`my-project.analytics.daily_user_segments`',\r\n        joinKey: ['event_date', 'user_pseudo_id'],\r\n        columns: ['segment'],\r\n        dedupe: true,\r\n    },\r\n],\r\n```\r\n\r\n**Example** — fix a promoted event parameter via enrichment (coalesce case: enrichment value wins where the JOIN matches, original kept where it doesn't):\r\n\r\n```javascript\r\n{\r\n    eventParamsToColumns: [{ name: 'page_title', type: 'string' }],\r\n    enrichments: [\r\n        {\r\n            name: 'titles',\r\n            level: 'row',\r\n            source: { schema: 'analytics', name: 'page_title_overrides' },\r\n            joinKey: 'page_location',\r\n            columns: ['page_title'],   // overlaps the promoted column → coalesce(enrich.page_title, event_data.page_title)\r\n        },\r\n    ],\r\n}\r\n```\r\n\r\n**Example** — item-level enrichment: attach product master data to each item via `item_id`. The enrichment flows into the `items` array struct; `margin_bucket` is added as a new item-struct field, and `item_category` overlap-coalesces against the original. Item-level enrichment columns do NOT appear at the row grain — they live inside `items[].<col>`:\r\n\r\n```javascript\r\nenrichments: [\r\n    {\r\n        name: 'products',\r\n        level: 'item',\r\n        source: { schema: 'analytics', name: 'product_master' },\r\n        joinKey: 'item_id',                                  // joins on item.item_id\r\n        columns: ['margin_bucket', 'item_category'],         // margin_bucket is additive; item_category overlap-coalesces\r\n    },\r\n],\r\n```\r\n\r\nFor `level: 'item'`, valid `joinKey` values are any field on the GA4 items struct (`item_id`, `item_category`, etc.) or any column on `event_data` (`user_pseudo_id`, `event_date`, etc.). A row-level and an item-level enrichment may share the same column name (e.g. both writing `cohort`) — the two columns target structurally distinct slots (`enhanced_events.cohort` at row grain vs `items[].cohort` inside the items array) and are not in collision.\r\n\r\n> **Note:** Each enrichment generates a CTE named `enrich_<name>` at the top of the pipeline. The `enrich_*` namespace is part of the reserved-names contract — `customSteps` cannot use these names. The active reserved set includes only the names of enrichments actually configured.\r\n\r\n> **Note:** Row-level enrichment columns get auto-generated descriptions (`Added by enrichment '<name>' (joined on <joinKey> from <source>).` for new columns; `Coalesced by enrichment '<name>' (...; falls back to original on missed JOIN). Original: <description>` for overlapping columns). User-supplied `dataformTableConfig.columns` overrides win — the auto-generated description is the default. Item-level enrichment columns do not receive auto-generated descriptions (BigQuery does not surface per-field descriptions on STRUCT-array fields cleanly through Dataform's column-description mechanism).\r\n\r\n> **Note:** `joinKey` and `columns` entries must be plain SQL identifiers — inline aliases like `'id as user_id'` are rejected at validation time. If your dim source uses a different column name, alias it in an upstream Dataform view and point `source` at that view.\r\n\r\n<br>\r\n\r\n---\r\n\r\n### Assertions\r\n\r\nThe package includes built-in data quality assertions that can be automatically created alongside the enhanced events table. Pass Dataform's `assert` function as the third argument to `createTable`:\r\n\r\n```javascript\r\nga4EventsEnhanced.createTable(publish, config, { assert });\r\n```\r\n\r\nThis creates the table along with the default-enabled assertions, using the same configuration:\r\n\r\n| Assertion | Name | Enabled by default | Description |\r\n| --------- | ---- | ------------------ | ----------- |\r\n| `dailyQuality` | `{tableName}_daily_quality` | Yes | Compares session count, event count, item revenue, and ecommerce purchase revenue per day between the enhanced table and raw export. Also reconciles item_revenue at the (event_date, item_id) grain on purchase events for days both sides consider final. Detects missing days, count mismatches, and non-final data inflation |\r\n\r\nThe assertion inherits the table's schema and tags from `dataformTableConfig` and queries the last 5 days of data.\r\n\r\n#### Selective Assertions\r\n\r\nDisable the assertion by setting it to `false`:\r\n\r\n```javascript\r\nga4EventsEnhanced.createTable(publish, config, {\r\n    assert,\r\n    assertions: { dailyQuality: false },\r\n});\r\n```\r\n\r\n#### Assertion Config Overrides\r\n\r\nOverride the assertion's Dataform configuration (name, schema, tags):\r\n\r\n```javascript\r\nga4EventsEnhanced.createTable(publish, config, {\r\n    assert,\r\n    assertions: {\r\n        dailyQuality: { tags: ['data_quality', 'ga4_export_fixer'] },\r\n    },\r\n});\r\n```\r\n\r\n#### Standalone Assertions (SQLX Deployment)\r\n\r\nFor SQLX deployments or when you need full control, assertions can also be used as standalone SQL generators:\r\n\r\n```javascript\r\nconst { ga4EventsEnhanced } = require('ga4-export-fixer');\r\n\r\nassert('daily_quality_check', {\r\n    schema: 'analytics_123456789',\r\n    tags: ['ga4_export_fixer'],\r\n}).query(ctx => {\r\n    return ga4EventsEnhanced.assertions.dailyQuality(\r\n        ctx.ref('ga4_events_enhanced_123456789'),\r\n        { ...config, sourceTable: ctx.ref(config.sourceTable) }\r\n    );\r\n});\r\n```\r\n\r\n<br>\r\n\r\n---\r\n\r\n### Creating Incremental Downstream Tables from `ga4_events_enhanced`\r\n\r\nSetting up incremental updates is easy using the **setPreOperations()** function. Just ensure that your result table includes the **data_is_final** flag from the **ga4_events_enhanced** table.\r\n\r\nThe **incrementalDateFilter()** function applies the same date filtering used by **ga4_events_enhanced**, based on the **config** options and the variables declared by **setPreOperations()**.\r\n\r\nKey fields such as session_id, user_id, and session_traffic_source_last_click are available as clean, sessionized versions that handle edge cases like sessions spanning midnight.\r\n\r\n**`definitions/ga4/ga4_sessions.sqlx`**\r\n\r\n```javascript\r\nconfig {\r\n  type: \"incremental\",\r\n  description: \"GA4 sessions table\",\r\n  schema: \"ga4_export_fixer\",\r\n  bigquery: {\r\n    partitionBy: \"event_date\",\r\n    clusterBy: ['session_id', 'data_is_final'],\r\n  },\r\n  tags: ['ga4_export_fixer']\r\n}\r\n\r\njs {\r\n  const { setPreOperations, helpers } = require('ga4-export-fixer');\r\n\r\n  const config = {\r\n    self: self(),\r\n    incremental: incremental(),\r\n    /*\r\n    Default options that can be overriden:\r\n    test: false,\r\n    testConfig: {\r\n        dateRangeStart: 'current_date()-1',\r\n        dateRangeEnd: 'current_date()',\r\n    },\r\n    preOperations: {\r\n        dateRangeStartFullRefresh: 'date(2000, 1, 1)',\r\n        dateRangeEnd: 'current_date()',\r\n        // incremental date range overrides allow re-processing only a subset of the data:\r\n        //incrementalStartOverride: undefined,\r\n        //incrementalEndOverride: undefined,\r\n    },\r\n    */\r\n  };\r\n}\r\n\r\nselect\r\n  event_date,\r\n  session_id,\r\n  user_pseudo_id,\r\n  user_id,\r\n  any_value(session_traffic_source_last_click.cross_channel_campaign) as session_traffic_source,\r\n  any_value(landing_page) as landing_page,\r\n  current_datetime() as row_inserted_timestamp,\r\n  min(data_is_final) as data_is_final\r\nfrom\r\n  ${ref('ga4_events_enhanced_298233330')}\r\nwhere\r\n  ${helpers.incrementalDateFilter(config)}\r\ngroup by \r\n  event_date,\r\n  session_id,\r\n  user_pseudo_id,\r\n  user_id\r\n\r\npre_operations {\r\n  ${setPreOperations(config)}\r\n}\r\n```\r\n\r\n<br>\r\n\r\n---\r\n\r\n### Helpers\r\n\r\nThe helpers contain templates for common SQL expressions. The functions are referenced by **ga4EventsEnhanced** but can also be imported as utility functions for working with GA4 data.\r\n\r\n```javascript\r\nconst { helpers } = require('ga4-export-fixer');\r\n```\r\n\r\n#### SQL Templates\r\n\r\n\r\n| Name        | Example             | Description                                                               |\r\n| ----------- | ------------------- | ------------------------------------------------------------------------- |\r\n| `eventDate` | `helpers.eventDate` | Casts `event_date` string to a DATE using YYYYMMDD format                 |\r\n| `sessionId` | `helpers.sessionId` | Builds a session ID by concatenating `user_pseudo_id` and `ga_session_id` |\r\n\r\n\r\n#### Functions\r\n\r\n**Unnesting parameters**\r\n\r\n\r\n| Function           | Example                                       | Description                                                                                                                                                                                  |\r\n| ------------------ | --------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `unnestEventParam` | `unnestEventParam('page_location', 'string')` | Extracts a value from the `event_params` array by key. Supported types: `'string'`, `'int'`, `'int64'`, `'double'`, `'float'`, `'float64'`. Omit type to get the value converted as a string |\r\n\r\n\r\n**Date and time**\r\n\r\n\r\n| Function                  | Example                                             | Description                                                                                                                              |\r\n| ------------------------- | --------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `getEventTimestampMicros` | `getEventTimestampMicros('custom_ts')`              | Returns SQL for event timestamp in microseconds. With a custom parameter, uses it (converted from ms) with fallback to `event_timestamp` |\r\n| `getEventDateTime`        | `getEventDateTime({ timezone: 'Europe/Helsinki' })` | Returns SQL for event datetime in the given timezone. Defaults to `'Etc/UTC'`                                                            |\r\n\r\n\r\n**Date filters**\r\n\r\n\r\n| Function              | Example                                                              | Description                                                                                            |\r\n| --------------------- | -------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------ |\r\n| `ga4ExportDateFilter` | `ga4ExportDateFilter('daily', 'current_date()-7', 'current_date()')` | Generates a `_table_suffix` filter for a single export type (`'daily'` or `'intraday'`) and date range |\r\n\r\n\r\n**Page details**\r\n\r\n\r\n| Function                | Example                                  | Description                                                                                                        |\r\n| ----------------------- | ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------ |\r\n| `extractUrlHostname`    | `extractUrlHostname('page_location')`    | Extracts hostname from a URL column                                                                                |\r\n| `extractUrlPath`        | `extractUrlPath('page_location')`        | Extracts the path component from a URL column                                                                      |\r\n| `extractUrlQuery`       | `extractUrlQuery('page_location')`       | Extracts the query string (including `?`) from a URL column                                                        |\r\n| `extractUrlQueryParams` | `extractUrlQueryParams('page_location')` | Parses URL query parameters into `ARRAY<STRUCT<key STRING, value STRING>>`                                         |\r\n| `extractPageDetails`    | `extractPageDetails()`                   | Returns a struct with `hostname`, `path`, `query`, and `query_params`. Defaults to `page_location` event parameter |\r\n\r\n\r\n**Aggregation**\r\n\r\n\r\n| Function         | Example                                                | Description                                                                                                                               |\r\n| ---------------- | ------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `aggregateValue` | `aggregateValue('user_id', 'last', 'event_timestamp')` | Aggregates a column using `'max'`, `'min'`, `'first'`, `'last'`, or `'any'`. `'first'` and `'last'` use the timestamp column for ordering |\r\n\r\n\r\n**Ecommerce**\r\n\r\n\r\n| Function             | Example                | Description                                                                                                                                 |\r\n| -------------------- | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `fixEcommerceStruct` | `fixEcommerceStruct()` | Cleans the ecommerce struct: sets `transaction_id` to null when `'(not set)'`, and fixes missing/NaN `purchase_revenue` for purchase events |\r\n\r\n\r\n**Data freshness**\r\n\r\n\r\n| Function      | Example                           | Description                                                                                                                                                                                           |\r\n| ------------- | --------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\r\n| `isFinalData` | `isFinalData('DAY_THRESHOLD', 3)` | Returns SQL that evaluates to `true` when data is final. `'DAY_THRESHOLD'` uses days since event (`dayThreshold` is required and must be a non-negative integer); `'EXPORT_TYPE'` checks table suffix |\r\n\r\n\r\n## License\r\n\r\nMIT","readmeFilename":"README.md"}