Google BigQuery Integration — Automate Google BigQuery with AI on Beauto

Google BigQuery is a fully managed data warehouse for large-scale data analytics, offering fast SQL queries and machine learning capabilities on massive datasets

Category: databases, analytics · 63 actions available

What you can automate with Google BigQuery

Beauto connects Google BigQuery with 900+ other apps so you can build AI-powered workflows in minutes. Trigger automations from Google BigQuery events, enrich Google BigQuery data with AI, or sync Google BigQuery with the rest of your stack — without writing code.

  • Sync Google BigQuery data with Gmail, Slack, Notion, HubSpot, Google Sheets, and more
  • Trigger AI agents on new Google BigQuery events and route the output anywhere
  • Schedule recurring Google BigQuery tasks — daily reports, cleanups, or bulk updates
  • Use natural language to describe the workflow; Beauto builds it for you

Google BigQuery actions Beauto supports

  • Cancel BigQuery Job — Tool to cancel a running BigQuery job. This call returns immediately, and you need to poll for the job status to see if the cancel completed successfully. Note that cancelled jobs may still incur costs.
  • Create Capacity Commitment — Tool to create a new capacity commitment resource in BigQuery Reservation. Use when you need to purchase compute capacity (slots) with a committed period of usage for BigQuery jobs. Supports various commitment plans (FLE
  • Create BigQuery Connection — Tool to create a new BigQuery connection to external data sources using the BigQuery Connection API. Use when setting up connections to AWS, Azure, Cloud Spanner, Cloud SQL, Salesforce DataCloud, or Apache Spark.
  • Create Analytics Hub Data Exchange — Tool to create a new Analytics Hub data exchange for sharing BigQuery datasets. Use when you need to set up a container for data sharing with descriptive information and listings.
  • Create Analytics Hub Listing — Tool to create a new listing in a BigQuery Analytics Hub data exchange. Use when you need to share a BigQuery dataset with specific subscribers or make it available for discovery. The dataset must exist and be in the sam
  • Create BigQuery Dataset — Tool to create a new BigQuery dataset with explicit location, labels, and description using the BigQuery Datasets API. Use when the workflow needs to set up a staging/warehouse dataset and correctness of region is critic
  • Create Analytics Hub Listing — Tool to create a new listing in a data exchange using Analytics Hub API. Use when publishing a BigQuery dataset to make it available for subscription by other users or organizations.
  • Create BigQuery Data Policy (v2beta1) — Tool to create a new data policy under a project with specified location using the v2beta1 BigQuery Data Policy API. Use when you need to set up data masking rules or column-level security for sensitive data. The v2beta1
  • Create Analytics Hub Query Template — Tool to create a new query template in a BigQuery Analytics Hub Data Clean Room (DCR) data exchange. Use when you need to define predefined and approved queries for data clean room use cases. Query templates must be crea
  • Create BigQuery Reservation — Tool to create a new BigQuery reservation resource to guarantee compute capacity (slots) for query and pipeline jobs. Use when you need to reserve dedicated compute resources for predictable performance and cost manageme
  • Create BigQuery Reservation Assignment — Tool to create a BigQuery reservation assignment that allows a project, folder, or organization to submit jobs using slots from a specified reservation. Use when setting up resource allocation for BigQuery workloads. Not
  • Create BigQuery Routine — Tool to create a new user-defined routine (function or procedure) in a BigQuery dataset. Use when you need to define SQL, JavaScript, Python, Java, or Scala functions/procedures for reusable logic, data transformations,
  • Create BigQuery Table — Tool to create a new, empty table in a BigQuery dataset. Use when setting up data infrastructure for standard tables, external tables, views, or materialized views. Supports partitioning, clustering, and encryption confi
  • Delete BigQuery Dataset — Tool to delete a BigQuery dataset specified by datasetId via the datasets.delete API. Before deletion, you must delete all tables unless deleteContents=True is specified. Use when cleaning up test datasets or removing un
  • Delete BigQuery Job Metadata — Tool to delete the metadata of a BigQuery job. Use when you need to remove job metadata from the system. If this is a parent job with child jobs, metadata from all child jobs will be deleted as well.
  • Delete BigQuery ML Model — Tool to delete a BigQuery ML model from a dataset. Use when you need to remove a trained machine learning model permanently. The operation deletes the model and cannot be undone.
  • Delete BigQuery Routine — Tool to delete a BigQuery routine by its ID. Use when you need to remove a stored procedure, user-defined function, or table function from a dataset. This operation is irreversible.
  • Delete BigQuery Table — Tool to delete a BigQuery table from a dataset. Use when you need to remove a table and all its data permanently. The operation deletes all data in the table and cannot be undone.
  • Get BigQuery ML Model — Tool to retrieve a specific BigQuery ML model resource by model ID. Use when you need detailed information about a trained machine learning model including its configuration, training runs, hyperparameters, and evaluatio
  • Get BigQuery Connection IAM Policy — Tool to get the IAM access control policy for a BigQuery connection resource. Returns an empty policy if the resource exists but has no policy set. Use this to check who has access to a specific connection before modifyi
  • Get BigQuery Dataset Metadata — Tool to retrieve BigQuery dataset metadata including location via the datasets.get API. Use this before creating jobs/queries if the workflow has been failing with location mismatch to confirm the dataset's region and co
  • Get BigQuery Job — Tool to retrieve information about a specific BigQuery job. Returns job configuration, status, and statistics. Use this to check job status after running queries or to get details about job execution.
  • Get BigQuery Query Results — Tool to get the results of a BigQuery query job via RPC. Use this to retrieve results after running a query, or to check job completion status and fetch paginated results.
  • Get BigQuery Routine — Tool to retrieve a BigQuery routine (user-defined function or stored procedure) by its ID. Use to inspect routine definitions, arguments, return types, and metadata.
  • Get BigQuery Routine IAM Policy — Tool to retrieve the IAM access control policy for a BigQuery routine resource. Returns an empty policy if the routine exists but has no policy set. Use this to check current access permissions before modifying them.
  • Get BigQuery Service Account — Tool to get the service account for a project used for interactions with Google Cloud KMS. Use when you need to retrieve the BigQuery service account email for KMS encryption configuration or key access permissions.
  • Get BigQuery Table IAM Policy — Tool to retrieve the IAM access control policy for a BigQuery table resource. Returns an empty policy if the resource exists but has no policy set. Use this to check current access permissions before modifying them.
  • Get BigQuery Table Schema — Tool to fetch a BigQuery table's schema and metadata without querying row data. Use before generating SQL queries to avoid column name typos and confirm field types and nullable modes. This is especially useful when INFO
  • Insert Data into BigQuery Table — Tool to stream data into BigQuery one record at a time without running a load job. Use when you need immediate data availability or inserting small batches. Supports row-level deduplication via insertId and error handlin
  • Insert BigQuery Job — Tool to start a new asynchronous BigQuery job (query, load, extract, or copy). Use when you need to run a query as a job, load data from Cloud Storage, extract table data to GCS, or copy tables. For dry-run validation wi
  • Insert BigQuery Job with Upload — Tool to start a new BigQuery load job with file upload. Uploads a file (CSV, JSON, etc.) and loads it into a BigQuery table in a single operation. Use when you need to upload data from a local file directly to BigQuery r
  • List Analytics Hub Listings — Tool to list all listings in a given Analytics Hub data exchange. Use when you need to discover available data listings within a specific data exchange that can be subscribed to for data sharing.
  • List BigQuery Connections — Tool to list BigQuery connections in a given project and location. Use when you need to discover available external data source connections (Cloud SQL, AWS, Azure, Spark, etc.) configured for BigQuery.
  • List BigQuery Capacity Commitments — Tool to list all capacity commitments for the admin project. Use when you need to view purchased compute capacity slots and their commitment details (plan, state, duration).
  • List Data Exchange Listings — Tool to list all listings in a given Analytics Hub data exchange using the v1beta1 API. Use when you need to discover available data listings within a specific data exchange that can be subscribed to for data sharing.
  • List BigQuery Datasets — Tool to list datasets in a specific BigQuery project, including dataset locations. Use after identifying an accessible project to discover available datasets and their locations before querying. The dataset location is c
  • List BigQuery Jobs — Tool to list all jobs that you started in a BigQuery project. Job information is available for a six month period after creation. Jobs are sorted in reverse chronological order by creation time. Use to monitor query exec
  • List BigQuery Data Transfer Locations — Tool to list information about supported locations for BigQuery Data Transfer Service. Use when you need to discover available regions/locations where BigQuery Data Transfer operations can be performed.
  • List Connections in Location — Tool to list BigQuery connections in a given project and location using the v1beta1 API. Use when you need to discover available external data source connections (Cloud SQL, AWS, Azure, Spark, etc.) configured for BigQue
  • List BigQuery Location Data Policies — Tool to list all data policies in a specified parent project and location using the v2beta1 API. Use when you need to discover data masking policies and column-level security policies configured for BigQuery datasets.

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