On January 27, 2021, Google is changing the required permissions for attaching IAM roles to service accounts. If you are using IAM roles for your Google service accounts, please see Changes to User Management.
- The browser appears when you select the BigQuery tab to create a dataset. See Import Data Page.
- For more information, see Using BigQuery.
- For more information on how data types are converted to and from BigQuery sources, see BigQuery Data Type Conversions.
If you have access to multiple projects:
- Reading: you can browse for BigQuery tables in other projects from which to read.
- Writing: you can browse for BigQuery databases that are accessible from other projects to which you have read and write access.
Enter the project identifier in the textbox, and click Go.
Tip: The identifiers for your projects are available from the Projects menu in the toolbar. See Projects Menu.
Tip: You can paste project identifiers from publicly available projects to read from them.
Use the links and icons to browse for databases and tables.
NOTE: Avoid using the Back button on your browser, which exits the browser without applying changes to your configuration.
NOTE: If you receive a Nothing Found error message when navigating to a BigQuery project to which you have access, please verify with your BigQuery administrator that the service account in use has been set up and has the proper permissions to access the project.
|Database||Click these links to open a BigQuery database to reveal its tables.|
Click the Plus icon to select this table as your source.
To preview its data, hover over the name of the table, and then click the Eye icon.
Tip: Sizes and update timestamps are calculated and displayed next to tables. They are not displayed next to databases.
Click the Plus icon to select this view as your source.
To preview its data, hover over the view name and then click the Eye icon.
NOTE: Previewing complex views may impact performance.
Use these links to navigate between pages of databases or tables.
NOTE: In some cases, subsequent pages of tables may be blank, and counts of tables may not match displayed figures. This is a known issue.
Click the links in the breadcrumb trail to navigate.
Create dataset with SQL
If needed, you can create imported datasets using SELECT statements applied to your BigQuery databases. Click Create dataset with SQL.
Tip: Using SQL to pre-filter your datasets can significantly reduce the volume of data that must be imported from the database.
For more information, see Create Dataset with SQL.
To filter the list of databases or tables, enter a string in the Search box. The filter is applied as you type and matches anywhere in the name of a currently displayed database or table name.
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