Explore BigQuery in the Google Cloud console

The Google Cloud console provides a graphical interface that you can use to create and manage BigQuery resources and tasks such as running SQL queries and creating pipelines.

Before you begin

Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector

1. Enable the BigQuery API.

   Roles required to enable APIs

   To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

   Enable the API

   For new projects, the BigQuery API is automatically enabled.

2. Optional: Enable billing for the project. If you don't want to enable billing or provide a credit card, the steps in this document still work. BigQuery provides you a sandbox to perform the steps. For more information, see Enable the BigQuery sandbox.
   Note: If your project has a billing account and you want to use the BigQuery sandbox, then disable billing for your project.

Open the Overview page in the Google Cloud console

Preview

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

Note: To provide feedback on the Overview page, click Help > Send feedback.

The BigQuery Overview page is your hub for discovering tutorials, features, and resources to help you get the most out of BigQuery. It provides guided paths for users of all skill levels, whether you are running your first query or exploring advanced AI/ML capabilities.

You can use the Overview page to find resources organized by your role or interest like data analysis or data science. This lets you find the most relevant content to get started quickly.

To open the Overview page, follow these steps.

1. Go to the Google Cloud console.

   Go to the Google Cloud console

2. In the Google Cloud console toolbar, click Navigation menu.

3. Click Solutions > All products.

4. In the Analytics section, click BigQuery.

5. In the navigation, click Overview.

You can also open the BigQuery Overview page by entering the following URL in your browser:

https://console.cloud.google.com/bigquery/overview

BigQuery opens in your most recently accessed project.

Overview page sections

The Overview page is divided into these sections:

• Introduction: The Introduction section that give you a quick overview of BigQuery's capabilities.

• Get started: The Get started section is designed for learning by doing. Here you can launch interactive guides that help you learn how to use BigQuery features.

• Find out more: The Find out more section shows the BigQuery release notes so you can view the latest feature announcements and updates.

• Explore possibilities: The Explore possibilities section provides in-depth tutorials and learning opportunities for specific features.

Customize the Overview page

In the top-right corner of the page is a filter bar. Click the role that best matches your current task or role:

• Data analysis
• Data science
• Data engineering
• Data administration

Selecting a task dynamically changes the content in the Introduction, Get started, and Explore Possibilities sections to show the most relevant content.

Hide irrelevant content

You can tailor the content on the Overview page to your specific needs by hiding individual cards within sections. To hide a card:

1. In the card, click More options.
2. Choose Hide card.
3. To unhide the card, at the end of the section, click Show hidden content.

If an entire section is not relevant, you can collapse it. Your preferences for collapsed sections and hidden cards are saved per user.

Open the BigQuery Studio page in the Google Cloud console

1. Go to the Google Cloud console.

   Go to the Google Cloud console

2. In the Google Cloud console toolbar, click Navigation menu.

3. Click Solutions > All products.

4. In the Analytics section, click BigQuery.

You can also open the BigQuery Studio page by entering the following URL in your browser:

https://console.cloud.google.com/bigquery

BigQuery opens in your most recently accessed project.

To simplify navigation, you can add (or pin) BigQuery as a top product in the navigation menu:

1. In the Google Cloud console navigation menu, hold the pointer over BigQuery.

2. Click Pin.

Overview of the BigQuery Studio page

The BigQuery Studio page has the following main sections:

• The BigQuery navigation menu
• The left pane
• The details pane
• The Add data dialog
• The home and query tabs

Navigation menu

In the BigQuery navigation menu, you can select any option from the following categories:

• Overview (Preview): The BigQuery Overview page is your new central hub for discovering tutorials, features, and resources to help you get the most out of BigQuery.

• Studio: displays your datasets, tables, and other BigQuery resources. In this workspace, you can perform common BigQuery tasks such as the following:

  • Create, run, save, and share queries and Colab Enterprise notebooks.
  • Work with tables, views, routines, and other BigQuery resources.
  • See your BigQuery job history.

• Search (Preview): lets you search for Google Cloud resources from BigQuery by using natural language queries.

• Pipelines and integration

  • Data transfers: lets you access the BigQuery Data Transfer Service to create and configure data transfers.

  • Pipelines (Dataform): displays a list of Dataform repositories that are created for your Google Cloud project.

  • Scheduled queries: displays your scheduled queries.

  • Scheduling: provides a list of pipelines and schedules for your Google Cloud project.

• Governance

  • Sharing (Analytics Hub): displays all of the data exchanges that you can access in your Google Cloud project.

  • Policy tags: displays a list of taxonomies that you can use to create hierarchical groups of policy tags.

  • Metadata curation: lets you scan data in Cloud Storage buckets to extract and then catalog metadata.

• Administration

  • Monitoring: lets you monitor operational health and resource utilization across an organization.

  • Jobs explorer: helps you monitor jobs activity across your organization.

  • Capacity management: displays slot commitments, reservations, and reservation assignments.

  • BI Engine: lets you manage reservation capacity for query optimization using BigQuery BI Engine.

  • Disaster recovery: displays failover reservations and failover datasets.

  • Recommendations: displays a list of recommendations in your organization or project.

• Migration

  • Assessment: lets you plan and review the migration of your existing data warehouse into BigQuery.

  • SQL translation: lets you convert your Teradata SQL queries so that they work in BigQuery.

• Additional resources

  • Partner Center: provides tools and services from partners to accelerate your workflow.

  • Settings (Preview): contain the following tabs:

    • My settings: let you set default settings that are applied when you start a session in BigQuery Studio. Some settings are inherited from your project or organization, but can be overridden on the My settings page.

    • Configuration settings: let BigQuery administrators customize the BigQuery Studio experience for users within the selected project or organization. This is achieved by showing or hiding user interface elements such as Save results > CSV (Google Drive), Open in > Looker Studio, and Export > Explore with Sheets. These settings don't restrict access to the underlying data and tools, even if they are hidden in BigQuery Studio. You need the bigquery.config.get permission to make changes at the organization level.

  • Release notes: contains the latest product updates and announcements for BigQuery.

  • You can control how the BigQuery navigation menu is displayed:

    • To collapse the navigation menu so that only the icons are visible, click Toggle BigQuery navigation menu.

    • To temporarily expand the menu when it's collapsed, hold the pointer over the menu.

    • To expand the menu so that the labels stay visible, click Toggle BigQuery navigation menu.

Left pane

The left pane is visible when you select Studio in the navigation menu. This pane consists of three panes: Explorer, Classic Explorer, and Git repository.

To collapse the left pane, click Collapse left pane. To expand the left pane, click Expand left pane.

Explorer pane

The Explorer pane lists different code assets and data resources. To open a new tab in the details pane, click a code asset type. This tab lists all files of that code asset type in your project. For example, click Notebooks to open the Notebooks tab, which lists all notebooks in your project. You can use the search bar or filters to find a file.

You can also go to the Home tab or open job histories and starred resources in a new tab.

You can use the search feature in the Explorer pane to find resources in BigQuery. The results appear in a new tab in the details pane. You can narrow your search by projects and resources types, such as Dataset. This search feature covers BigQuery resources in your organization, while the Google Cloud toolbar's search feature covers all of Google Cloud.

Classic Explorer pane

This pane lists current Google Cloud projects and any starred projects.

To view the resources in your projects and datasets, do the following:

• To view the datasets that you have access to in a project, expand the project.

• To view tables, views, and functions in a dataset, expand the dataset.

You can also use the search box to search for resources by name (dataset, table, or view name) or by label within your current and starred projects. The search feature finds the resources that directly match, or contain matches, to your search query. It might not show all the resources in the matched resource's level. To see all the resources, click Show more.

Git repository pane

Preview

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

Note: To provide feedback or ask questions that are related to this Preview feature, contact [e-mail].

You can use repositories to perform version control on files that you use in BigQuery. BigQuery uses Git to record changes and manage file versions. For more information, see Introduction to repositories.

You can use workspaces within repositories to edit the code stored in the repository. When you click a workspace in the Git repository pane, it opens in a tab in the details pane. For more information, see Introduction to workspaces.

Details pane

The details pane shows information about your BigQuery resources. When you select a dataset, table, view, or other resource in the Classic Explorer pane, a new tab is displayed in the details pane. On these tabs, you can view information about the resource, or you can create tables and views, modify table schemas, export data, and perform other actions.

You can drag the tab to the edge of the editor to open it in a new column so that you can compare the tabs, or drag the tab to a different position in the current or an adjacent column. This feature is in preview.

In the query editor, you can run an interactive query and explore the results in the Query results pane that opens after you run the query.

When you navigate through tabs, the resource corresponding to the focused tab is selected in the Classic Explorer pane. If you open BigQuery using your workspace URL, then your workspace query editor tab opens, and the corresponding resource is selected in the Classic Explorer pane.

You can use the search bar in the Google Cloud toolbar to search for resources (projects, datasets, or tables), documentation, and products (such as Compute Engine and Cloud Storage) across Google Cloud. You might need permissions, similar to BigQuery permissions, to access resources in different products.

Add data dialog

In the Add data dialog, you can use search and filtering capabilities to find a data source that you want to work with. After you select a data source, you can do the following based on the capabilities available for your data source.

• Set up BigQuery table over external data (Federation): enables BigQuery to access external data without ingesting it into BigQuery. You can create a table to access external data or create a connection to an external source.

• Load data to BigQuery: lets you load data to BigQuery by setting up a data transfer service or by using a partner capability. Loading data to BigQuery is recommended for optimal data processing at scale.

• Change data capture to BigQuery: replicates data from a data source to BigQuery by capturing and applying changes. You can use applications such as datastream or partner solutions to ingest data from a data source.

• Stream data to BigQuery: ingests data into BigQuery with low latency. You can use applications such as dataflow, Pub/Sub, or partner solutions to ingest data from a data source.

For more information about loading data into BigQuery, see Introduction to loading data.

Additionally, you can Access and query public datasets.

Home and query tabs

The first time you open the BigQuery page, you see the home tab and a query editor tab, with the home tab in focus. The home tab contains the following:

• The Check out what's new in Studio section that lists new features in BigQuery Studio. You can click Try it to view the features. If the section isn't visible, click What's new in Studio to expand the section.

• The Create new section that has options to create a new SQL query, notebook, Apache Spark notebook, data canvas, data preparation file, pipeline, or table.

• The Recent section where you can view your 10 most recently accessed resources.

• The following demo guides:

  • Run a sample query on a public dataset from Google Trends.

  • Run a Colab notebook that walks you through the basics of BigQuery DataFrames.

  • Run a Spark notebook that walks you through the basics of Spark in BigQuery.

  • Add data to BigQuery.

You can close the home tab. To go back to the home tab, click *Home in the Explorer pane.

To open a query editor from the home tab, click SQL query. To access ways to import data and search data sources that work with BigQuery, click Add data.

If you open BigQuery using your workspace URL, then your workspace query editor tab opens first.

Display resources

The Explorer pane lists datasets that you can browse in your current project or any projects that you starred. Consider the following when displaying resources:

• To display the datasets in a project, click Toggle node for that project, and then click Datasets. A new tab opens in the details tab with a list of all the datasets in the project. Click the dataset to see its details.
• To display the tables, views, and functions in a dataset, click Overview > Tables. You can also view a dataset's details, models, and routines in other tabs.

• You can also use breadcrumbs to seamlessly navigate through different tabs and resources, as shown in the following screenshot:

  

• To reduce tab proliferation, clicking a resource opens it within the same tab. To open the resource in a separate tab, press Ctrl (or Command on macOS) and click the resource. To prevent the current tab from getting its content replaced, double-click the tab name (you will notice that its name changes from italicized to regular font). If you still lose your resource, click tab_recent Recent tabs in the details pane to find the resource.

Star resources

If you have important or current projects, datasets, or tables, you can star them in the Classic Explorer pane. To star a resource, hold the pointer over the name of the resource that you want to star, and then click Star.

View starred resources

To view the starred resources, click Starred in the Explorer pane. A new tab containing a list of all starred resources appears.

If you want to view all the resources as a resource tree, click the Classic Explorer pane, and turn off the Show starred only toggle.

Unstar resources

To unstar a resource, go to the Classic Explorer pane, and then click Unstar next to the resource.

View recently accessed resources

In the Google Cloud console, you can view your 10 most recently accessed resources. These resources include tables, saved queries, models, and routines.

When you create or update a resource in the console or query editor, the resource is marked as recent. For a recently opened resource to be marked as recent, you have to open it in the workspace tab. If you run a query on a resource, then the resource is not marked as recent.

To view your recently accessed resources, follow these steps:

1. In the Google Cloud console, go to the BigQuery page.

2. Ensure that you are on the BigQuery home page. If necessary, click Home in the Explorer pane.

   In the Recent section, you see your 10 recently accessed resources.

Work with tabs

You can control how you work with tabs in the details pane.

Split two tabs

Whenever you select a resource or click Compose new query in the details pane, a new tab opens. If more than one tab is open, you can split the tabs into two panes and view them side by side.

To split tabs into two panes, follow these steps:

1. Next to the tab name, click Open menu.

2. Select one of the following options:

   • To place the selected tab in the left pane, select Split tab to left.
   • To place the selected tab in the right pane, select Split tab to right.
   Note: If only one tab is open, these menu options are unavailable.

To unsplit the tabs, select Open menu on one of the open tabs, and then select Move tab to left pane or Move tab to right pane.

To split tabs when querying tables, follow these steps:

1. In the Explorer menu, click the table that you want to query.

2. Click Query, and then click In new tab or In split tab:

   

3. Click the field name that you want to query:

   

The following image shows the details pane with two open tabs. One tab has a SQL query, and the other tab shows details about a table.

Move a tab

To move a tab from one pane to the other pane, follow these steps:

1. Next to the tab name, click Open menu.

2. Select Move tab to right pane or Move tab to left pane (whichever option is available).

Close a tab

To close all tabs except for one, follow these steps:

1. Next to the tab name, click Open menu.

2. Select Close other tabs.

View personal and project history

Every time you load, export, query, or copy data, BigQuery automatically creates, schedules, and runs a job that tracks the progress of the task. To view job histories of your current billing project, do the following:

1. Go to the BigQuery page.

   Go to BigQuery

2. In the left pane, click Explorer:

   

3. In the Explorer pane, click Job history.

   This opens the list of job histories in a new tab:

   

4. To view details of your own jobs, click Personal history.

5. To view details of recent jobs in your project, click Project history.

To see the details of a job or to open the query in an editor, do the following:

1. In the Actions column for a job or query, click Actions.

2. Select Show job details or View job in editor.

For more information about managing jobs, see Manage jobs.

Keyboard shortcuts

To view shortcuts in the Google Cloud console, click BigQuery Studio shortcuts. The following keyboard shortcuts are supported in the Google Cloud console:

Action	Windows or Linux shortcut	macOS shortcut
Create a new tab	Ctrl+Alt+t	Cmd+Option+t
Close tab (keyboard focused tab)	Delete or Backspace	Delete or Backspace
Format query	Ctrl+Shift+f	Cmd+Shift+f
Gemini code completion and generation	Ctrl+Shift+Space	Ctrl+Shift+Space
Jump to a specific tab	Ctrl+Alt+1 through 8	Cmd+Option+1 through 8
Jump to last tab	Ctrl+Alt+9	Cmd+Option+9
Jump to next open tab	Ctrl+Alt+Tab or Ctrl+Alt+PgDn	Cmd+Shift+Option+Right arrow
Jump to previous open tab	Ctrl+Alt+Shift+Tab or Ctrl+Alt+PgUp	Cmd+Shift+Option+Left arrow
Move tab left	Ctrl+Alt+Shift+PgUp	Ctrl+Shift+Option+PgUp
Move tab right	Ctrl+Alt+Shift+PgDn	Ctrl+Shift+Option+PgDn
Open tab menu (keyboard focused tab)	Shift+F10	Shift+F10
Run query or highlighted query	Ctrl+Enter or Ctrl+e	Cmd+Enter or Cmd+e
See list of editor shortcuts	F1	F1
Split or move active tab to left	Ctrl+Alt+[	Cmd+Option+[
Split or move active tab to right	Ctrl+Alt+]	Cmd+Option+]
SQL autosuggest	Tab or Ctrl+Space	Tab or Ctrl+Space
SQL generation tool	Ctrl+Shift+P	Cmd+Shift+P
Toggle line comment	Ctrl+/	Cmd+/

What's next

• To learn about querying a public dataset and using the BigQuery sandbox, see Try BigQuery using the sandbox.
• To learn how to load and query data in the Google Cloud console, see Load and query data.