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List Tables returns all tables within a BigQuery project or specific dataset. Essential for discovering available data, planning data workflows, and managing your BigQuery table inventory.

When to Use It

  • Discover available tables before building data workflows
  • Find specific tables for dynamic workflow construction
  • Use it as AI Tool for AI Agents to understand your data structure
  • Audit table usage and organization across projects

Inputs

FieldTypeRequiredDescription
ProjectSelectYesGoogle BigQuery project to search in
DatasetSelectNoSpecific dataset to list tables from (optional - lists all if empty)
LimitNumberNoMaximum number of tables to return (1-1000)

Outputs

OutputDescription
Tables ListList of all tables with names, types, and metadata

Credit Cost

1 credit per operation.

Real-World Examples

BigQuery AI Agent:
AI Agent → List Datasets → List Tables → Run Query
"Allow AI to discover all available datasets and tables, then run SQL queries"
Data Discovery for New Projects:
List Tables → AI Analyze Data → Write to Sheets
"Explore available marketing data tables before building analytics workflow"

Understanding Table Information

The returned data includes: Table Metadata:
  • Table ID and full name
  • Table type (TABLE, VIEW, EXTERNAL)
  • Creation and modification timestamps
  • Dataset and project information
  • Row count and size information (when available)
Table Types:
  • Standard Tables: Regular BigQuery tables with stored data
  • Views: Virtual tables based on SQL queries
  • External Tables: Tables that reference data outside BigQuery

FAQ

Without a dataset, you get all tables across all datasets in the project. With a dataset selected, you get only tables from that specific dataset. Use dataset filtering for focused exploration.
You’ll receive table name, type (table/view/external), creation date, modification date, project and dataset info, and basic metadata like row counts when available.
No, you’ll only see tables that your connected Google account has permission to view. Restricted tables won’t appear in the results.
Use the List Tables results with other workflow nodes like Conditional Split or AI Analyze Data to filter by table name patterns, creation dates, or other metadata.
Increase the limit parameter up to 1000, use dataset filtering to narrow results, or run multiple queries. Consider if you need all tables for your specific use case.
Regular table inventory helps track data growth, identify unused tables, ensure proper naming conventions, and maintain organized data architecture for compliance.
The metadata includes basic size and activity information. Combine results with AI Analyze Data to identify patterns or use Conditional Split to filter by specific criteria.
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