This document shows you how to use table explorer to examine table data
and create data exploration queries.
About table explorer
Table explorer offers an automated way to visually explore table data and
create queries based on your selection of table fields.
In table explorer, you select table fields to examine.
You can select up to 10 table fields at a time.
Table explorer displays the selected fields
as interactive cards with the list of up to 10 most common values for
each field, sorted by the count column. You can interact with the cards by
selecting fields and distinct values which you want to examine more closely.
Table explorer creates a data exploration query based on your selection.
You can copy this query into a new query in query editor,
or apply the query in table explorer. When you apply the query, table explorer
runs it and refreshes the displayed cards with query results. To continue table
data exploration, select more fields or values from the refreshed cards.
Limitations
Table explorer is available for BigQuery tables,
BigLake tables, external tables, and views.
Table explorer lets you explore a single table at a time. The feature does
not support simultaneous exploration of multiple tables or
generating cross-table operations, for example, JOIN operations.
Table explorer creates SQL queries that directly reflect your
selection of table fields and distinct values. You can execute
queries created by table explorer or manually edit them in the query editor.
Table explorer does not provide AI-powered assistance to generate,
complete, or explain SQL queries.
To explore table data and generate queries for tables with column-level
access control (ACLs) or restricted user permissions, you must have read access
for all selected fields. To run the generated queries, you must
have sufficient permissions.
Pricing
Table explorer runs queries based on your selection of table fields
and distinct values to display table exploration results.
These queries incur compute pricing charges. Table explorer displays the
amount of data that will be processed for each
query before you confirm your selection of table fields,
triggering the query execution.
You can also incur compute charges
if you run a query generated by table explorer.
For more information about BigQuery compute pricing, see
Pricing.
Before you begin
In the Trusted Cloud console, on the project selector page,
select or create a Trusted Cloud project.
To get the permissions that
you need to view table data and generate queries with table explorer,
ask your administrator to grant you the
following IAM roles:
These predefined roles contain
the permissions required to view table data and generate queries with table explorer. To see the exact permissions that are
required, expand the Required permissions section:
Required permissions
The following permissions are required to view table data and generate queries with table explorer:
bigquery.jobs.create
on the project from which the query is being run, regardless of where the data is stored.
bigquery.tables.getData
on all tables and views that you want to explore.
In the Explorer pane, select the table for which you want to create
a query.
Click the Table explorer tab, and then click Select fields.
In the Select fields pane, select up to 10 table fields to explore.
For a partitioned table, in the Partitioning filter section,
set a custom partitioning filter. Partition filters can reduce the billable
compute when exploring tables.
Select Apply custom partitioning filter.
In the displayed settings fields, configure the partitioning filter.
Display of filter settings depends on the partition type of the table:
hour, day, month, year, or range.
Click Save.
When you click Save, BigQuery runs a query to
display common values for the selected fields, which incurs charges.
You can see the amount of data which will be processed at the top of the
Select fields pane.
Table explorer displays the selected fields as cards in a list of up to
the ten most common values sorted by the Count column.
In the Generated Query section, you can see a query
which you can run to show the same data.
Optional: To modify your results, you can try the following:
In the displayed selected field cards,
select distinct values to further filter the data.
To revert all changes, click Reset.
In the Generated Query section, click Copy to query to copy the
generated code into a new, untitled query in the query editor. In the newly
created query tab, you can edit, run, and manage the query.
To run the generated query, click Apply.
BigQuery executes the generated query and refreshes
displayed cards with results of the query.
To continue table exploration, select new fields or distinct values from
the refreshed displayed cards.
Troubleshooting
Access Denied: Project [project_id]: User does not have bigquery.jobs.create
permission in project [project_id].
This error occurs when a principal lacks permission to create a query jobs in the project.
Resolution: An administrator must grant you the bigquery.jobs.create
permission on the project you are querying. This permission is required in
addition to any permission required to access the queried data.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-25 UTC."],[[["\u003cp\u003eTable Explorer provides a visual and automated way to examine table data and create queries by selecting fields and values.\u003c/p\u003e\n"],["\u003cp\u003eUsers can select up to 10 table fields at a time, and the tool displays common values and generates a query based on these selections.\u003c/p\u003e\n"],["\u003cp\u003eTable Explorer is available for BigQuery tables, BigLake tables, external tables, and views, but is limited to exploring one table at a time, without support for cross-table operations.\u003c/p\u003e\n"],["\u003cp\u003eUsing Table Explorer involves compute pricing charges, as queries are run based on the user's selection of fields and values, and users must have specific IAM roles, including BigQuery Job User and BigQuery Data Viewer.\u003c/p\u003e\n"],["\u003cp\u003eTo explore data with column-level access control, users must have read access to all selected fields, and the tool doesn't have AI-powered assistance for generating, completing, or explaining SQL queries.\u003c/p\u003e\n"]]],[],null,["# Create queries with table explorer\n==================================\n\n|\n| **Preview**\n|\n|\n| This feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n\nTo request support or provide feedback for this feature, email\n[bq-studio-product-team@google.com](mailto:bq-studio-product-team@google.com).\n\nThis document shows you how to use table explorer to examine table data\nand create data exploration queries.\n\nAbout table explorer\n--------------------\n\nTable explorer offers an automated way to visually explore table data and\ncreate queries based on your selection of table fields.\n\nIn table explorer, you select table fields to examine.\nYou can select up to 10 table fields at a time.\n\nTable explorer displays the selected fields\nas interactive cards with the list of up to 10 most common values for\neach field, sorted by the `count` column. You can interact with the cards by\nselecting fields and distinct values which you want to examine more closely.\nTable explorer creates a data exploration query based on your selection.\n\nYou can copy this query into a new query in query editor,\nor apply the query in table explorer. When you apply the query, table explorer\nruns it and refreshes the displayed cards with query results. To continue table\ndata exploration, select more fields or values from the refreshed cards.\n\nLimitations\n-----------\n\n- Table explorer is available for BigQuery tables, BigLake tables, external tables, and views.\n- Table explorer lets you explore a single table at a time. The feature does not support simultaneous exploration of multiple tables or generating cross-table operations, for example, `JOIN` operations.\n- Table explorer creates SQL queries that directly reflect your selection of table fields and distinct values. You can execute queries created by table explorer or manually edit them in the query editor. Table explorer does not provide AI-powered assistance to generate, complete, or explain SQL queries.\n- To explore table data and generate queries for tables with column-level access control (ACLs) or restricted user permissions, you must have read access for all selected fields. To run the generated queries, you must have sufficient [permissions](#roles).\n\nPricing\n-------\n\nTable explorer runs queries based on your selection of table fields\nand distinct values to display table exploration results.\nThese queries incur compute pricing charges. Table explorer displays the\namount of data that will be processed for each\nquery before you confirm your selection of table fields,\ntriggering the query execution.\n\nYou can also incur compute charges\nif you run a query generated by table explorer.\n\nFor more information about BigQuery compute pricing, see\n[Pricing](/bigquery/pricing).\n\nBefore you begin\n----------------\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **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.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the BigQuery API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=bigquery.googleapis.com)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **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.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the BigQuery API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=bigquery.googleapis.com)\n\n\u003cbr /\u003e\n\n### Required roles and permissions\n\n\nTo get the permissions that\nyou need to view table data and generate queries with table explorer,\n\nask your administrator to grant you the\nfollowing IAM roles:\n\n- [BigQuery Job User](/iam/docs/roles-permissions/bigquery#bigquery.jobUser) (`roles/bigquery.jobUser`) on the project.\n- [BigQuery Data Viewer](/iam/docs/roles-permissions/bigquery#bigquery.dataViewer) (`roles/bigquery.dataViewer`) on all tables and views that you want to explore.\n\n\nFor more information about granting roles, see [Manage access to projects, folders, and organizations](/iam/docs/granting-changing-revoking-access).\n\n\nThese predefined roles contain\n\nthe permissions required to view table data and generate queries with table explorer. To see the exact permissions that are\nrequired, expand the **Required permissions** section:\n\n\n#### Required permissions\n\nThe following permissions are required to view table data and generate queries with table explorer:\n\n- ` bigquery.jobs.create` on the project from which the query is being run, regardless of where the data is stored.\n- ` bigquery.tables.getData` on all tables and views that you want to explore.\n\n\nYou might also be able to get\nthese permissions\nwith [custom roles](/iam/docs/creating-custom-roles) or\nother [predefined roles](/iam/docs/roles-overview#predefined).\n\nFor more information about BigQuery Identity and Access Management (IAM),\nsee [Access control with IAM](/bigquery/docs/access-control).\n\nExplore data in a table to create a query\n-----------------------------------------\n\nTo explore table data and create a query based on your selection of table\nfields and values, follow these steps:\n\n1. In the Google Cloud console, go to BigQuery Studio.\n\n [Go to BigQuery Studio](https://console.cloud.google.com/bigquery)\n2. In the **Explorer** pane, select the table for which you want to create\n a query.\n\n3. Click the **Table explorer** tab, and then click **Select fields**.\n\n4. In the **Select fields** pane, select up to 10 table fields to explore.\n\n5. For a partitioned table, in the **Partitioning filter** section,\n set a custom partitioning filter. Partition filters can reduce the billable\n compute when exploring tables.\n\n 1. Select **Apply custom partitioning filter**.\n\n 2. In the displayed settings fields, configure the partitioning filter.\n\n Display of filter settings depends on the partition type of the table:\n hour, day, month, year, or range.\n6. Click **Save**.\n\n When you click **Save** , BigQuery runs a query to\n display common values for the selected fields, which incurs charges.\n You can see the amount of data which will be processed at the top of the\n **Select fields** pane.\n\n Table explorer displays the selected fields as cards in a list of up to\n the ten most common values sorted by the `Count` column.\n In the **Generated Query** section, you can see a query\n which you can run to show the same data.\n7. Optional: To modify your results, you can try the following:\n\n 1. In the displayed selected field cards, select distinct values to further filter the data.\n 2. To revert all changes, click **Reset**.\n 3. In the **Generated Query** section, click **Copy to query** to copy the generated code into a new, untitled query in the query editor. In the newly created query tab, you can edit, run, and manage the query.\n8. To run the generated query, click **Apply**.\n\n BigQuery executes the generated query and refreshes\n displayed cards with results of the query.\n9. To continue table exploration, select new fields or distinct values from\n the refreshed displayed cards.\n\nTroubleshooting\n---------------\n\n Access Denied: Project [project_id]: User does not have bigquery.jobs.create\n permission in project [project_id].\n\nThis error occurs when a principal lacks permission to create a query jobs in the project.\n\n**Resolution** : An administrator must grant you the `bigquery.jobs.create`\npermission on the project you are querying. This permission is required in\naddition to any permission required to access the queried data.\n\nFor more information about BigQuery permissions, see\n[Access control with IAM](/bigquery/docs/access-control).\n\nWhat's next\n-----------\n\n- Learn how to [explore your data by generating data insights](/bigquery/docs/data-insights).\n- Learn how to [write queries with Gemini assistance in BigQuery](/bigquery/docs/write-sql-gemini).\n- Learn how to iterate on query results with natural language questions by using [data canvas](/bigquery/docs/data-canvas)."]]
