이 문서에서는 BigQuery의 Colab Enterprise 노트북을 소개합니다. 노트북을 사용하여 SQL, Python, 기타 일반적인 패키지 및 API로 분석 및 머신러닝(ML) 워크플로를 완료할 수 있습니다. 노트북은 다음 옵션을 통한 향상된 공동작업 및 관리를 제공합니다.
Identity and Access Management(IAM)를 사용하여 특정 사용자 및 그룹과 노트북을 공유합니다.
노트북 버전 기록을 검토합니다.
이전 버전의 노트북으로 되돌리거나 브랜치를 만듭니다.
노트북은 Dataform으로 구동되는 BigQuery Studio 코드 애셋입니다.
저장된 쿼리도 코드 애셋입니다.
모든 코드 애셋은 기본 리전에 저장됩니다. 기본 리전을 업데이트하면 해당 시점 이후에 생성된 모든 코드 애셋의 리전이 변경됩니다.
노트북 런타임은 노트북에서 코드 실행을 사용 설정하기 위해 특정 사용자에게 할당되는 Compute Engine 가상 머신입니다. 여러 노트북이 동일한 런타임을 공유할 수 있습니다. 그러나 각 런타임은 사용자 한 명에게만 속하며 다른 사용자는 사용할 수 없습니다. 노트북 런타임은 일반적으로 관리자 권한이 있는 사용자가 정의하는 템플릿을 기반으로 생성됩니다. 언제든지 다른 템플릿 유형을 사용하는 런타임으로 변경할 수 있습니다.
노트북 보안
Identity and Access Management(IAM) 역할을 사용하여 노트북에 대한 액세스를 제어합니다. 자세한 내용은 노트북에 액세스 권한 부여를 참조하세요.
지원되는 리전
BigQuery Studio를 사용하면 노트북 버전을 저장, 공유, 관리할 수 있습니다. 다음 표에는 BigQuery Studio를 사용할 수 있는 리전이 나와 있습니다.
BigQuery Studio 노트북의 가격 책정 정보는 노트북 런타임 가격 책정을 참조하세요.
슬롯 사용량 모니터링
Google Cloud 콘솔에서 Cloud Billing 보고서를 보고 BigQuery Studio 노트북 슬롯 사용량을 모니터링할 수 있습니다. Cloud Billing 보고서에서 라벨이 goog-bq-feature-type이고 값이 BQ_STUDIO_NOTEBOOK인 필터를 적용하여 BigQuery Studio 노트북의 슬롯 사용량과 비용을 봅니다.
[[["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: 2025-08-26(UTC)"],[[["\u003cp\u003eBigQuery notebooks facilitate analysis and machine learning workflows through SQL, Python, and other tools, offering enhanced collaboration features like sharing, version history, and branching.\u003c/p\u003e\n"],["\u003cp\u003eNotebooks are code assets within BigQuery Studio, powered by Dataform, and are integrated with BigQuery DataFrames for scalable data analysis using pandas and scikit-learn.\u003c/p\u003e\n"],["\u003cp\u003eNotebooks provide assistive code development through Gemini AI, auto-completion of SQL statements, and data visualization via matplotlib and seaborn libraries.\u003c/p\u003e\n"],["\u003cp\u003eNotebooks use Colab Enterprise runtimes, which are user-specific Compute Engine virtual machines that can be shared by multiple notebooks but not by multiple users.\u003c/p\u003e\n"],["\u003cp\u003eAccess to notebooks is controlled via Identity and Access Management (IAM), and pricing information for notebook runtimes and slot usage can be monitored via Cloud Billing reports.\u003c/p\u003e\n"]]],[],null,["# Introduction to notebooks\n=========================\n\nThis document provides an introduction to\n[Colab Enterprise notebooks](/colab/docs/introduction)\nin BigQuery. You can use notebooks to complete\nanalysis and machine learning (ML) workflows by using SQL, Python, and other\ncommon packages and APIs. Notebooks offer improved collaboration and management\nwith the following options:\n\n- Share notebooks with specific users and groups by using Identity and Access Management (IAM).\n- Review the notebook version history.\n- Revert to or branch from previous versions of the notebook.\n\nNotebooks are [BigQuery Studio](/bigquery/docs/query-overview#bigquery-studio)\ncode assets powered by [Dataform](/dataform/docs/overview).\n[Saved queries](/bigquery/docs/saved-queries-introduction) are also code assets.\nAll code assets are stored in a default\n[region](#supported_regions). Updating the default region changes\nthe region for all code assets created after that point.\n\nNotebook capabilities are available only in the Google Cloud console.\n\nBenefits\n--------\n\nNotebooks in BigQuery offer the following benefits:\n\n- [BigQuery DataFrames](/python/docs/reference/bigframes/latest) is integrated into notebooks, no setup required. BigQuery DataFrames is a Python API that you can use to analyze BigQuery data at scale by using the [pandas DataFrame](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html) and [scikit-learn](https://scikit-learn.org/stable/modules/classes.html) APIs.\n- Assistive code development powered by [Gemini generative AI](/bigquery/docs/write-sql-gemini).\n- Auto-completion of SQL statements, the same as in the BigQuery editor.\n- The ability to save, share, and manage versions of notebooks.\n- The ability to use [matplotlib](https://matplotlib.org/), [seaborn](https://seaborn.pydata.org/), and other popular libraries to visualize data at any point in your workflow.\n\nRuntime management\n------------------\n\nBigQuery uses\n[Colab Enterprise runtimes](/colab/docs/create-runtime) to run\nnotebooks.\n\nA notebook runtime is a Compute Engine virtual machine allocated to a\nparticular user to enable code execution in a notebook. Multiple notebooks can\nshare the same runtime. However, each runtime belongs to only one user and can't\nbe used by others. Notebook runtimes are created based on template, which are\ntypically defined by users with administrative privileges. You can change to a\nruntime that uses a different template type at any time.\n\nNotebook security\n-----------------\n\nYou control access to notebooks by using Identity and Access Management (IAM) roles. For\nmore information, see\n[Grant access to notebooks](/bigquery/docs/create-notebooks#grant_access_to_notebooks).\n\nTo detect vulnerabilities in Python packages that you use in your notebooks,\ninstall and use\n[Notebook Security Scanner](/security-command-center/docs/enable-notebook-security-scanner)\n([Preview](/products#product-launch-stages)).\n\nSupported regions\n-----------------\n\nBigQuery Studio lets you save, share, and manage versions of\nnotebooks. The following table lists the regions where BigQuery Studio is\navailable:\n\nPricing\n-------\n\nFor pricing information about BigQuery Studio notebooks, see [Notebook runtime pricing](/bigquery/pricing#external_services).\n\nMonitor slot usage\n------------------\n\nYou can monitor your BigQuery Studio notebook slot usage by viewing your [Cloud Billing report](/billing/docs/reports) in the Google Cloud console. In the Cloud Billing report, apply a filter with the label **goog-bq-feature-type** with the value **BQ_STUDIO_NOTEBOOK** to view slot usage and costs from BigQuery Studio notebook.\n\nTroubleshooting\n---------------\n\nFor more information, see [Troubleshoot Colab Enterprise](/colab/docs/troubleshooting).\n\nWhat's next\n-----------\n\n- Learn how to [create notebooks](/bigquery/docs/create-notebooks).\n- Learn how to [manage notebooks](/bigquery/docs/manage-notebooks)."]]
낮은 CO2
