Introduction to notebooks

This document provides an introduction toColab Enterprise notebooksin BigQuery. You can use notebooks to completeanalysis and machine learning (ML) workflows by using SQL, Python, and othercommon packages and APIs. Notebooks offer improved collaboration and managementwith the following options:

• Share notebooks with specific users and groups by usingIdentity and Access Management (IAM).
• Review the notebook version history.
• Revert to or branch from previous versions of the notebook.

Notebooks areBigQuery Studiocode assets powered byDataform.Saved queries are also code assets.All code assets are stored in a defaultregion. Updating the default region changesthe region for all code assets created after that point.

Notebook capabilities are available only in the Google Cloud console.

Benefits

Notebooks in BigQuery offer the following benefits:

• BigQuery DataFrames isintegrated into notebooks, no setup required. BigQuery DataFrames isa Python API that you can use to analyze BigQuery data atscale by using thepandas DataFrameandscikit-learn APIs.
• Assistive code development powered byGemini generative AI.
• Auto-completion of SQL statements, the same as in theBigQuery editor.
• The ability to save, share, and manage versions of notebooks.
• The ability to usematplotlib,seaborn, and other popularlibraries to visualize data at any point in your workflow.
• The ability to write andexecute SQLin a cell that can reference Python variables from your notebook.
• InteractiveDataFrame visualizationthat supports aggregation and customization.

Notebook gallery

Preview

This feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of theService Specific Terms. Pre-GA features are available "as is" and might have limited support. For more information, see thelaunch stage descriptions.

Note: To provide feedback or to request product enhancements, contactbigquery-notebook-gallery@google.com.

The notebook gallery is a central hub for discovering and using prebuiltnotebook templates. These templates let you perform common tasks like datapreparation, data analysis, and visualization. Notebook templates also help youexplore BigQuery Studio features, manage workflows, and promote bestpractices.

You can use notebook gallery templates to streamline your entireintent-to-insights workflow across each stage of the data lifecycle-fromingestion and exploration to advanced analytics and BigQuery ML.

The notebook gallery provides templates for every skill level. The galleryincludes fundamental templates for SQL, Python, Apache Spark, andDataFrames. You can also explore topics like generative AI and multimodal dataanalytics in BigQuery.

To get started with the notebook gallery, follow these steps:

1. Go to theBigQuery page.

   Go to BigQuery

2. From from the BigQuery Studio home page, clickView notebookgallery.

   

For more information on using notebook gallery templates, seeCreate a notebook using the notebook gallery.

Runtime management

BigQuery usesColab Enterprise runtimes to runnotebooks.

A notebook runtime is a Compute Engine virtual machine allocated to aparticular user to enable code execution in a notebook. Multiple notebooks canshare the same runtime. However, each runtime belongs to only one user and can'tbe used by others. Notebook runtimes are created based on template, which aretypically defined by users with administrative privileges. You can change to aruntime that uses a different template type at any time.

Notebook security

You control access to notebooks by using Identity and Access Management (IAM) roles. Formore information, seeGrant access to notebooks.

To detect vulnerabilities in Python packages that you use in your notebooks,install and useNotebook Security Scanner(Preview).

Supported regions

BigQuery Studio lets you save, share, and manage versions ofnotebooks. The following table lists the regions where BigQuery Studio isavailable:

	Region description	Region name	Details
Africa
	Johannesburg	africa-south1
Americas
	Columbus	us-east5
	Dallas	us-south1	Low CO2
	Iowa	us-central1	Low CO2
	Las Vegas	us-west4
	Los Angeles	us-west2
	Mexico	northamerica-south1
	Montréal	northamerica-northeast1	Low CO2
	North Virginia	us-east4
	Oklahoma	us-central2	Low CO2
	Oregon	us-west1	Low CO2
	Salt Lake City	us-west3
	Santiago	southamerica-west1	Low CO2
	São Paulo	southamerica-east1	Low CO2
	South Carolina	us-east1
	Toronto	northamerica-northeast2	Low CO2
Asia Pacific
	Bangkok	asia-southeast3
	Delhi	asia-south2
	Hong Kong	asia-east2
	Jakarta	asia-southeast2
	Melbourne	australia-southeast2
	Mumbai	asia-south1
	Osaka	asia-northeast2
	Seoul	asia-northeast3
	Singapore	asia-southeast1
	Sydney	australia-southeast1
	Taiwan	asia-east1
	Tokyo	asia-northeast1
Europe
	Belgium	europe-west1	Low CO2
	Berlin	europe-west10
	Finland	europe-north1	Low CO2
	Frankfurt	europe-west3
	London	europe-west2	Low CO2
	Madrid	europe-southwest1	Low CO2
	Milan	europe-west8
	Netherlands	europe-west4	Low CO2
	Paris	europe-west9	Low CO2
	Stockholm	europe-north2	Low CO2
	Turin	europe-west12
	Warsaw	europe-central2
	Zürich	europe-west6	Low CO2
Middle East
	Dammam	me-central2
	Doha	me-central1
	Tel Aviv	me-west1

Pricing

For pricing information about BigQuery Studio notebooks, seeNotebook runtime pricing.

Monitor slot usage

You can monitor your BigQuery Studio notebook slot usage by viewing yourCloud Billing report in the Google Cloud console. In the Cloud Billing report, apply a filter with the labelgoog-bq-feature-type with the valueBQ_STUDIO_NOTEBOOK to view slot usage and costs from BigQuery Studio notebook.

Troubleshooting

For more information, seeTroubleshoot Colab Enterprise.

What's next

• Learn how tocreate notebooks.
• Learn how tomanage notebooks.