BigQuery API가 사용 설정된 Google Cloud 프로젝트에 액세스해야 합니다.
새 Google Cloud 프로젝트를 만들거나 기존 프로젝트의 BigQuery API를 사용 설정하려면
BigQuery 빠른 시작 가이드의 시작하기 전에 섹션을
완료하세요.
BigQuery 샌드박스 모드는 무료로 사용할 수 있으며 특정 제한사항이 있습니다.
무료 사용량 등급으로 충분히 데이터 세트를 살펴보고 샘플 쿼리를
실행할 수 있습니다. 원하는 경우 결제를 사용 설정하여 무료 사용량 등급을 넘어설 수도 있습니다.
제한사항
이 데이터 세트에는 실제 데이터 세트를 에뮬레이션하는 난독화된 데이터가 포함되어 있습니다.
은 실제 Google 애널리틱스 구현에서 비롯된 것처럼 보입니다. 특정 필드에는
<Other>, NULL, '' 등 자리표시자 값이 포함됩니다. 난독화로 인해 데이터 세트의 내부 일관성이 다소 제한될 수 있습니다.
데이터 세트는 Google Merchandise Store의 Google 애널리틱스 데모 계정과 데이터가 다르므로 비교할 수 없습니다.
데이터 세트 사용
Cloud Console은 테이블 쿼리를 위한 인터페이스를 제공합니다. BigQuery UI를 사용하여
ga4_obfuscated_sample_ecommerce 데이터 세트에 액세스할 수 있습니다.
편집기 탭이 표시되지 않으면 add_box새 쿼리 작성을 클릭합니다.
다음 쿼리를 복사하여 편집기 필드에 붙여넣습니다. 이 쿼리는
데이터 세트의 순 이벤트 수, 사용자 수, 일수를 표시합니다.
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_*`
유효한 쿼리의 경우 쿼리에서 처리할 데이터의 양과 함께 체크표시가 나타납니다. 이 측정항목을 통해 쿼리 실행 비용을
확인할 수 있습니다.
[null,null,["최종 업데이트: 2024-09-12(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/)."]]
