이 문서에서는 Google Cloud를 위한 Gemini 제품군에 포함된 BigQuery의 Gemini에서 데이터 작업에 도움이 되는 AI 기반 지원을 제공하는 방법을 설명합니다.
Gemini in BigQuery에 대한 AI 지원
BigQuery의 Gemini는 다음 작업을 수행하는 데 도움이 되는 AI 지원을 제공합니다.
데이터 통계로 데이터 탐색 및 이해 데이터 통계는 테이블 메타데이터에서 생성된 유용한 쿼리를 사용하여 패턴을 발견하고 통계 분석을 수행할 수 있는 직관적이고 자동화된 방법을 제공합니다. 이 기능은 특히 초기 데이터 탐색 분석의 콜드 스타트 문제를 해결하는 데 유용합니다. 자세한 내용은 BigQuery에서 데이터 통계 생성을 참조하세요.
BigQuery 데이터 캔버스로 데이터 탐색, 변환, 쿼리, 시각화. BigQuery의 Gemini로 자연어를 사용하여 테이블 애셋을 찾고 조인하고 쿼리하고 결과를 시각화하며 전체 프로세스에서 다른 사용자와 원활하게 공동작업할 수 있습니다. 자세한 내용은 데이터 캔버스로 분석을 참조하세요.
지원 SQL 및 Python 데이터 분석 받기. BigQuery의 Gemini를 사용하여 SQL 또는 Python에서 코드를 생성하거나 제안하고 기존 SQL 쿼리를 설명할 수 있습니다. 자연어 쿼리를 사용하여 데이터 분석을 시작할 수도 있습니다. 코드를 생성, 완성, 요약하는 방법은 다음 문서를 참조하세요.
분석을 위한 데이터 준비. BigQuery의 데이터 준비 기능을 사용하면 분석을 위해 데이터를 정리하는 데 도움이 되는 컨텍스트 인식 AI 생성 변환 추천을 받을 수 있습니다. 자세한 내용은 Gemini로 데이터 준비를 참조하세요.
변환 규칙으로 SQL 변환 맞춤설정. (프리뷰) 대화형 SQL 변환기를 사용할 때 SQL 변환을 맞춤설정하는 Gemini 고급 변환 규칙을 만듭니다.
자연어 프롬프트를 사용하여 SQL 변환 출력 변경사항을 설명하거나 SQL 패턴을 지정하여 찾고 바꿀 수 있습니다. 자세한 내용은 변환 규칙 만들기를 참조하세요.
정확한 결과를 제공하려면 BigQuery의 Gemini가 향상된 기능을 위해 BigQuery의 고객 데이터 및 메타데이터 모두에 액세스해야 합니다. BigQuery의 Gemini를 사용 설정하면 Gemini에 테이블 및 쿼리 기록을 포함한 이 데이터에 액세스할 수 있는 권한이 부여됩니다. BigQuery의 Gemini는 모델을 학습시키거나 미세 조정하는 데 사용자 데이터를 사용하지 않습니다. Gemini에서 사용자 데이터를 사용하는 방법에 대한 자세한 내용은 Google Cloud 를 위한 Gemini에서 사용자 데이터를 사용하는 방법을 참조하세요.
BigQuery의 Gemini 고급 기능은 다음과 같습니다.
SQL 생성 도구
SQL 쿼리를 생성하는 프롬프트
SQL 쿼리 작성
SQL 쿼리 설명
Python 코드 생성
Python 코드 완성
데이터 캔버스
데이터 준비
데이터 통계
위치
Gemini에서 사용자 데이터를 처리하는 위치에 대한 자세한 내용은 Gemini 제공 위치를 참조하세요.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-09-04(UTC)"],[[["\u003cp\u003eGemini in BigQuery offers AI-powered assistance to explore, understand, and analyze your data by using data insights, and data canvas features.\u003c/p\u003e\n"],["\u003cp\u003eYou can utilize Gemini in BigQuery to generate, complete, and explain SQL and Python code, as well as translate SQL code.\u003c/p\u003e\n"],["\u003cp\u003eGemini in BigQuery helps optimize your data infrastructure with recommendations for partitioning, clustering, and materialized views.\u003c/p\u003e\n"],["\u003cp\u003eWith Gemini in BigQuery you can use the Data preparation tool to get AI-generated data transformation recommendations to prepare your data for analysis.\u003c/p\u003e\n"],["\u003cp\u003eGemini in BigQuery allows for advanced troubleshooting of serverless Apache Spark workloads by explaining job errors and offering actionable recommendations.\u003c/p\u003e\n"]]],[],null,["# Gemini in BigQuery overview\n\nThis document describes how Gemini in BigQuery, which is part\nof the [Gemini for Google Cloud](/gemini/docs/overview) product suite,\nprovides AI-powered assistance to help you work with your data.\n\nAI assistance with Gemini in BigQuery\n-------------------------------------\n\nGemini in BigQuery provides AI assistance to help\nyou do the following:\n\n- **Explore and understand your data with data insights** . Data insights offers an automated, intuitive way to uncover patterns and perform statistical analysis by using insightful queries that are generated from the metadata of your tables. This feature is especially helpful in addressing the cold-start challenges of early data exploration. For more information, see [Generate data insights in BigQuery](/bigquery/docs/data-insights).\n- **Discover, transform, query, and visualize data with BigQuery data canvas** . You can use natural language with Gemini in BigQuery, to find, join, and query table assets, visualize results, and seamlessly collaborate with others throughout the entire process. For more information, see [Analyze with\n data canvas](/bigquery/docs/data-canvas).\n- **Get assisted SQL and Python data analysis** . You can use Gemini in BigQuery to generate or suggest code in either SQL or Python, and to explain an existing SQL query. You can also use natural language queries to begin data analysis. To learn how to generate, complete, and summarize code, see the following documentation: \n - SQL code assist\n - [Use the SQL generation tool](/bigquery/docs/write-sql-gemini#use_the_sql_generation_tool)\n - [Prompt to generate SQL queries](/bigquery/docs/write-sql-gemini#chat)\n - [Generate SQL queries with Gemini Cloud Assist](/bigquery/docs/write-sql-gemini#chat) ([Preview](/products#product-launch-stages))\n - [Complete a SQL query](/bigquery/docs/write-sql-gemini#complete_a_sql_query) ([Preview](/products#product-launch-stages))\n - [Explain a SQL query](/bigquery/docs/write-sql-gemini#explain_a_sql_query)\n - Python code assist\n - [Generate Python code with the code generation tool](/bigquery/docs/write-sql-gemini#generate_python_code)\n - [Generate Python code with Gemini Cloud Assist](/bigquery/docs/write-sql-gemini#chat-python) ([Preview](/products#product-launch-stages))\n - [Python code completion](/bigquery/docs/write-sql-gemini#python_code_completion)\n - [Generate BigQuery DataFrames Python code](/bigquery/docs/write-sql-gemini#dataframe) ([Preview](/products#product-launch-stages))\n- **Prepare data for analysis** . Data preparation in BigQuery gives you context aware, AI-generated transformation recommendations to cleanse data for analysis. For more information, see [Prepare data with Gemini](/bigquery/docs/data-prep-get-suggestions).\n- **Customize your SQL translations with translation rules** . ([Preview](/products#product-launch-stages)) Create Gemini-enhanced translation rules to customize your SQL translations when using the [interactive SQL translator](/bigquery/docs/interactive-sql-translator). You can describe changes to the SQL translation output using natural language prompts or specify SQL patterns to find and replace. For more information, see [Create a translation\n rule](/bigquery/docs/interactive-sql-translator#create_a_translation_rule).\n\nGemini for Google Cloud doesn't use your prompts or its\nresponses as data to train its models without your express permission. For more\ninformation about how Google uses your data, see\n[How Gemini for Google Cloud uses your data](/gemini/docs/discover/data-governance).\n| As an early-stage technology, Gemini for Google Cloud\n| products can generate output that seems plausible but is factually incorrect. We recommend that you\n| validate all output from Gemini for Google Cloud products before you use it.\n| For more information, see\n| [Gemini for Google Cloud and responsible AI](/gemini/docs/discover/responsible-ai).\n| **Note** : Gemini in BigQuery is part of Gemini for Google Cloud and doesn't support the same compliance and security offerings as BigQuery. You should only set up Gemini in BigQuery for BigQuery projects that don't require [compliance offerings that aren't supported by Gemini for Google Cloud](/gemini/docs/discover/certifications). For information about how to turn off or prevent access to Gemini in BigQuery, see [Turn off Gemini for Google Cloud products](/gemini/docs/turn-off-gemini).\n\nPricing\n-------\n\nSee [Gemini for Google Cloud pricing](/products/gemini/pricing).\n\nQuotas and limits\n-----------------\n\nFor quotas and limits that apply to Gemini in BigQuery,\nsee [Gemini for Google Cloud quotas and limits](/gemini/docs/quotas).\n\nWhere to interact with Gemini in BigQuery\n-----------------------------------------\n\nAfter you [set up Gemini in BigQuery](/gemini/docs/bigquery/set-up-gemini),\nyou can use Gemini in BigQuery to do the following\nin BigQuery Studio:\n\n- To [generate data insights](/bigquery/docs/data-insights#insights-bigquery-table), go to the **Insights** tab for a table entry, where you can identify patterns, assess quality, and run statistical analysis across your BigQuery data.\n- To use data canvas, [create a data canvas or use data canvas](/bigquery/docs/data-canvas#work-with-data-canvas) from a table or query to explore data assets with natural language and share your canvases.\n- To use natural language to generate SQL or Python code, or receive suggestions with autocomplete while typing, use the **SQL generation tool** for your [SQL queries](/bigquery/docs/write-sql-gemini#generate_a_sql_query) or [Python code](/bigquery/docs/write-sql-gemini#python_code_completion). Gemini in BigQuery can also explain your SQL code in natural language.\n- To prepare data for analysis, in the **Create new** list, select **Data preparation** . For more information, see [Open the data preparation editor in BigQuery](/bigquery/docs/data-prep-get-suggestions#open-data-prep-editor).\n\nSet up Gemini in BigQuery\n-------------------------\n\nFor detailed setup steps, see\n[Set up Gemini in BigQuery](/gemini/docs/bigquery/set-up-gemini).\n\nHow Gemini in BigQuery uses your data\n-------------------------------------\n\nIn order to provide accurate results, Gemini in\nBigQuery requires access to both your\n[Customer Data](/terms/data-processing-addendum) and metadata\nin BigQuery for enhanced features. Enabling Gemini\nin BigQuery grants Gemini permission to access\nthis data, which includes your tables and query history. Gemini\nin BigQuery doesn't use your data to train or fine-tune its\nmodels. For more information on how Gemini uses your data, see\n[how Gemini for Google Cloud uses your data](/gemini/docs/discover/data-governance).\n\nEnhanced features in Gemini in BigQuery are the following:\n\n- SQL generation tool\n- Prompt to generate SQL queries\n- Complete a SQL query\n- Explain a SQL query\n- Generate python code\n- Python code completion\n- Data canvas\n- Data preparation\n- Data insights\n\n### Locations\n\nFor information about where Gemini processes your data, see\n[Gemini serving locations](/gemini/docs/locations).\n\nWhat's next\n-----------\n\n- See the latest enhancements and fixes in [release notes](/gemini/docs/release-notes).\n- Learn how to [set up Gemini in BigQuery](/gemini/docs/bigquery/set-up-gemini).\n- Learn how to [write queries with Gemini assistance](/bigquery/docs/write-sql-gemini).\n- Learn more about [Google Cloud compliance](/security/compliance)."]]