Debes tener acceso a un proyecto de Google Cloud con la API de BigQuery habilitada.
Completa la sección Antes de empezar de la guía de inicio rápido de BigQuery para crear un proyecto de Google Cloud o para habilitar la API de BigQuery en un proyecto que ya tengas.
Este conjunto de datos contiene datos ofuscados que emulan el aspecto de un conjunto de datos real a partir de una implementación real de Google Analytics 4. Algunos campos incluyen valores de marcadores de posición, como <Other>, NULL y ''. Debido a la ofuscación, la coherencia interna del conjunto de datos podría ser algo limitada.
La consola de Cloud proporciona una interfaz para consultar tablas. Puedes usar la interfaz de BigQuery para acceder al conjunto de datos de ga4_obfuscated_sample_ecommerce.
Si no se muestra la pestaña del editor, haz clic en add_boxRedactar nueva consulta.
Copia y pega la siguiente consulta en el campo del editor. Esta consulta mostrará el número de eventos, usuarios y días únicos del conjunto de datos.
SELECT
COUNT(*) AS event_count,
COUNT(DISTINCT user_pseudo_id) AS user_count,
COUNT(DISTINCT event_date) AS day_count
FROM `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*`
Si la consulta es válida, aparecerá una marca de verificación junto con la cantidad de datos que procesará la consulta. Esta métrica te ayuda a determinar el coste de ejecutar la consulta.
Haz clic en Ejecutar. La página de resultados de la consulta aparecerá debajo de la ventana de consulta.
[null,null,["Última actualización: 2024-04-17 (UTC)."],[[["\u003cp\u003eThe \u003ccode\u003ega4_obfuscated_sample_ecommerce\u003c/code\u003e dataset provides obfuscated Google Analytics event export data for the Google Merchandise Store from November 1, 2020 to January 31, 2021.\u003c/p\u003e\n"],["\u003cp\u003eThis public dataset can be accessed and queried using BigQuery, allowing users to explore and analyze ecommerce website behavior.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset uses placeholder values for certain fields due to obfuscation, and its internal consistency may be limited.\u003c/p\u003e\n"],["\u003cp\u003eUsers can explore the dataset through the BigQuery UI, sample queries, and advanced analytical tools like Connected Sheets and Looker Studio.\u003c/p\u003e\n"],["\u003cp\u003eBefore using the dataset, ensure you have a Google Cloud project with BigQuery API enabled and review the limitations of the dataset.\u003c/p\u003e\n"]]],["The core content describes the `ga4_obfuscated_sample_ecommerce` dataset, a sample of Google Merchandise Store's obfuscated ecommerce data from November 2020 to January 2021. Access requires a Google Cloud project with BigQuery API enabled. Users can query the dataset using the BigQuery UI by composing and running queries in the editor. A sample query to count unique events, users, and days is provided. Users can then explore further by using advanced queries, schema, and other tools.\n"],null,["# BigQuery sample dataset for Google Analytics ecommerce web implementation\n\n[Google Merchandise Store](https://shop.googlemerchandisestore.com) is an online store that sells Google-branded\nmerchandise. The site uses Google Analytics's standard web [ecommerce\nimplementation](/tag-manager/ecommerce-ga4) along with [enhanced measurement](https://support.google.com/analytics/answer/9216061). The\n[`ga4_obfuscated_sample_ecommerce` dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=ga4_obfuscated_sample_ecommerce&t=events_20210131&page=table) available through the BigQuery\nPublic Datasets program contains a sample of obfuscated BigQuery event export\ndata for three months from 2020-11-01 to 2021-01-31.\n\nPre-requisite\n-------------\n\n- You need access to a Google Cloud project with BigQuery API enabled.\n Complete the *Before you begin* section in the [BigQuery Quickstart guide](https://cloud.google.com/bigquery/docs/quickstarts/quickstart-web-ui#before-you-begin) to\n create a new Google Cloud project or to enable the BigQuery API in an\n existing one.\n\n- You can use the [BigQuery Sandbox mode](https://cloud.google.com/bigquery/docs/sandbox) for free with certain limitations.\n The [Free usage tier](https://cloud.google.com/bigquery/pricing#free-tier) should be sufficient to explore this dataset and run the\n sample queries. You can optionally [Enable Billing](https://cloud.google.com/billing/docs/how-to/modify-project) to go beyond the Free\n usage tier.\n\nLimitations\n-----------\n\nThis dataset contains obfuscated data that emulates what a real world dataset\nwould look like from an actual Google Analytics implementation. Certain fields\nwill contain placeholder values including `\u003cOther\u003e`, `NULL`, and `''`. Due to\nobfuscation, internal consistency of the dataset might be somewhat limited.\n\nThe dataset can not be compared to the [Google Analytics Demo Account](https://support.google.com/analytics/answer/6367342) for\nGoogle Merchandise store as the data is different.\n\nUsing the dataset\n-----------------\n\n1. The Cloud Console provides an interface to query tables. You can use the\n [BigQuery UI](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=ga4_obfuscated_sample_ecommerce&t=events_20210131&page=table) to access the `ga4_obfuscated_sample_ecommerce` dataset.\n\n2. If the **Editor** tab isn't visible, then click add_box **Compose new query**.\n\n3. Copy and paste the following query into the Editor field. This query will\n show to number of unique events, users, and days in the dataset.\n\n SELECT\n COUNT(*) AS event_count,\n COUNT(DISTINCT user_pseudo_id) AS user_count,\n COUNT(DISTINCT event_date) AS day_count\n FROM `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*`\n\n4. For valid queries, a check mark will appear along with the amount of data\n that the query will process. This metric helps you determine the cost of\n running the query. \n\n \u003cbr /\u003e\n\n5. Click **Run** . The query results page will appear below the query window. \n\n \u003cbr /\u003e\n\n6. Try running some [sample queries](/analytics/bigquery/basic-queries).\n\nNext Steps\n----------\n\n- Learn more about the schema for [Google Analytics BigQuery event export\n schema](/analytics/bigquery/event-schema).\n\n- Run some of the [advanced queries](/analytics/bigquery/advanced-queries) on the dataset.\n\n- If you are not familiar with BigQuery, explore [BigQuery How-to Guides](https://cloud.google.com/bigquery/docs/how-to).\n\n- Use [Connected Sheets](https://cloud.google.com/bigquery/docs/connected-sheets) to analyze the dataset from Google Sheets\n spreadsheet.\n\n- [Visualize](https://cloud.google.com/bigquery/docs/visualize-looker-studio) the dataset using [Looker Studio](https://lookerstudio.google.com/)."]]