Add Google BigQuery to your AI agent
Google BigQuery is a fully managed data warehouse for large-scale data analytics, offering fast SQL queries and machine learning capabilities on massive datasets
- Things your agent can do in Google BigQuery
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Things your AI can do in Google BigQuery
Your FormWise AI can handle any of these in Google BigQuery — on its own, without you needing to click a button.
Create Analytics Hub Listing
PopularTool 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 same region as the data exchange.
Create BigQuery Dataset
PopularTool 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 critical to avoid downstream job location mismatches. Surfaces 409 Already Exists errors cleanly without retrying.
Create BigQuery Routine
PopularTool 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, or custom masking. Supports scalar functions, table-valued functions, procedures, and aggregate functions with comprehensive type definitions.
Create BigQuery Table
PopularTool 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 configuration.
Delete BigQuery Dataset
PopularTool 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 unused data warehouses. Immediately after deletion, you can create another dataset with the same name.
Delete BigQuery ML Model
PopularTool 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 Table
PopularTool 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 Dataset Metadata
PopularTool 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 correct the job location accordingly.
Get BigQuery Job
PopularTool 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
PopularTool 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 Table Schema
PopularTool 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 INFORMATION_SCHEMA access is restricted.
Insert Data into BigQuery Table
PopularTool 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 handling via skipInvalidRows.
Show 51 more things it can do
Insert BigQuery Job
PopularTool 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 without execution, set dryRun to true in configuration.
Insert BigQuery Job with Upload
PopularTool 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 rather than loading from Cloud Storage.
List BigQuery Datasets
PopularTool 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 critical for avoiding location-related query/job errors.
List BigQuery Jobs
PopularTool 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 execution, track job statuses, and retrieve job history.
List BigQuery Models
PopularTool to list all BigQuery ML models in a specified dataset. Requires READER dataset role. Use this to discover available models before getting detailed information via models.get method.
List BigQuery Projects
PopularTool to list BigQuery projects to which the user has been granted any project role. Returns projects with at least READ access. For enhanced capabilities, consider using the Resource Manager API.
List BigQuery Table Data
PopularTool to list the content of a BigQuery table in rows via the REST API. Use this to retrieve actual data from a table without writing SQL queries. Returns paginated results with row data in the native BigQuery format.
List BigQuery Tables
PopularTool to list tables in a BigQuery dataset via the REST API. Use this early in exploration to discover accessible tables without relying on INFORMATION_SCHEMA, especially when SQL-based metadata queries are blocked or restricted. This provides a deterministic inventory of tables even when dataset-level permissions prevent INFORMATION_SCHEMA access.
Patch BigQuery Dataset
PopularTool to update an existing BigQuery dataset using RFC5789 PATCH semantics. Only replaces fields provided in the request, leaving other fields unchanged. Use when you need to modify dataset properties like description, labels, expiration settings, or access controls without affecting other configuration.
Patch BigQuery ML Model
PopularTool to update specific fields in an existing BigQuery ML model using PATCH semantics. Use when you need to modify model metadata like description, friendly name, labels, or expiration time without replacing the entire model resource.
Patch BigQuery Table
PopularTool to update specific fields in an existing BigQuery table using RFC5789 PATCH semantics. Only the fields provided in the request are updated; unspecified fields remain unchanged. Use when you need to modify table metadata like description, friendly name, labels, or expiration time without replacing the entire table resource.
Undelete BigQuery Dataset
PopularTool to undelete a BigQuery dataset within the time travel window. If a deletion time is specified, the dataset version deleted at that time is undeleted; otherwise, the most recently deleted version is restored.
Update BigQuery Dataset
PopularTool to update information in an existing BigQuery dataset using the PUT method. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. Use when you need to modify dataset properties like description, access controls, or default settings.
Update BigQuery Table
PopularTool to update an existing BigQuery table. The update method replaces the entire Table resource, whereas the patch method only replaces fields that are provided. Use when you need to modify table properties like schema, description, labels, partitioning, or clustering configuration.
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 (FLEX, MONTHLY, ANNUAL, THREE_YEAR) and editions (STANDARD, ENTERPRISE, ENTERPRISE_PLUS).
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 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 endpoint uses a nested request structure.
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 created in DCR data exchanges only.
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 management. Reservations can be configured with autoscaling, concurrency limits, and edition-based features.
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. Note: A resource can only have one assignment per (job_type, location) combination.
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 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.
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 evaluation metrics.
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 modifying permissions.
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.
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 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 BigQuery in a specific location.
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.
List Organization Data Exchanges
Tool to list all data exchanges from projects in a given organization and location using Analytics Hub API. Use when you need to discover available data exchanges within an organization that can be used for data sharing.
List Analytics Hub Query Templates
Tool to list all query templates in a given Analytics Hub data exchange. Use when you need to discover available query templates that define predefined and approved queries for data clean room use cases.
List BigQuery Reservation Assignments
Tool to list BigQuery reservation assignments. Only explicitly created assignments will be returned (no expansion or merge happens). Use wildcard "-" in parent path to list assignments across all reservations in a location.
List BigQuery Reservation Groups
Tool to list all BigQuery reservation groups for a project in a specified location. Use when you need to discover available reservation groups which serve as containers for reservations.
List BigQuery Reservations
Tool to list all BigQuery reservations for a project in a specified location. Use when you need to discover available reservations or view reservation details including slot capacity and autoscale configuration.
List BigQuery Routines
Tool to list all routines (user-defined functions and stored procedures) in a BigQuery dataset. Requires the READER dataset role. Use this to discover available routines before executing or inspecting them.
List BigQuery Row Access Policies
Tool to list all row access policies on a specified BigQuery table. Use when you need to discover which row-level security policies are applied to a table and their filter predicates.
Query
Query Tool runs a SQL query in BigQuery using the REST API. Use proper BigQuery SQL syntax, e.g., SELECT * FROM `project.dataset.table` WHERE column_name = 'value'. Results are returned under data.rows; an empty rows array means no matching data. Large result sets may be returned via remote_file_info instead of inline rows. Verify exact project_id, dataset, table, and column names before running; wrong identifiers trigger invalidQuery or notFound errors.
Search All BigQuery Reservation Assignments
Tool to search all BigQuery reservation assignments for a specified resource in a particular region. Use when you need to find assignments for a project, folder, or organization. Returns assignments created on the resource or its closest ancestor, covering all JobTypes.
Set BigQuery Routine IAM Policy
Tool to set the IAM access control policy for a BigQuery routine resource. Use this to grant or modify access permissions for users, service accounts, or groups. Include the etag from getIamPolicy to prevent concurrent modifications.
Test BigQuery Routine IAM Permissions
Tool to test which IAM permissions the caller has on a BigQuery routine. Returns the subset of requested permissions that the caller actually has. Use to verify access before performing operations.
Update BigQuery Connection
Tool to update a specified BigQuery connection using the BigQuery Connection API. Use when you need to modify connection properties such as friendly name, description, or connection-specific settings. For security reasons, credentials are automatically reset if connection properties are included in the update mask.
Update BigQuery Routine
Tool to update an existing BigQuery routine (function or stored procedure). This replaces the entire routine resource with the provided definition. Use when modifying routine logic, arguments, return types, or other configuration. Ensure all required fields are provided as this is a full replacement operation.
Built for the way you actually work
No code, no engineers
Connect in a few clicks and start using your AI right away. If you can use the apps you already love, you can do this.
Sounds like you, not like a bot
Train your AI on your offer, your voice, and the way you actually talk to clients — it picks up where you leave off.
Plugs into the stack you already use
No need to rip out your CRM, your scheduler, or your email tool. Your AI works inside the apps running your business today.
Your data stays yours
Client conversations, lists, and credentials are scoped to your workspace. Nothing gets shared, sold, or used to train anyone else’s AI.
What you can do once Google BigQuery is connected
Onboard new clients without lifting a finger
When someone signs up, your AI greets them, sets up their next step in Google BigQuery, and keeps the momentum going — even at 2am.
Reply to leads in seconds, not days
Your AI watches Google BigQuery for new inquiries, answers questions in your voice, and books the call before they cool off.
Get your weekends back
Hand off the repetitive Google BigQuery work — follow-ups, reminders, updates, simple admin — and stop being the bottleneck in your own business.
How to connect Google BigQuery to your agent
- 1
Start using FormWise for free
Sign up in under a minute.
- 2
Find Google BigQuery in your connected apps
Inside FormWise, go to Settings → Connected Services and look for Google BigQuery.
- 3
Hit "Connect"
Click "Connect Google BigQuery" and log in like you normally would. We only ask for the permissions your AI actually needs.
- 4
Tell your AI what to do in Google BigQuery
Build a quick AI Agent (it's like writing instructions, not code), and pick the Google BigQuery actions you want your AI to handle.
- 5
Watch it run
Send it a real-world task and watch your AI take care of Google BigQuery for you. Tweak the wording until it feels just right.
Powered by the AI you already trust
Your Google BigQuery workflow runs on the same world-class AI used by ChatGPT, Claude, and Gemini. We handle the technical part — you just tell your AI what to do, in plain English.
- OpenAI
- Anthropic Claude
- Google Gemini
Questions other Google BigQuery users had before signing up
Do I need to know how to code?
Not even a little. If you can use Google BigQuery today, you can set this up. You'll connect Google BigQuery, tell your AI what it should help with, and you're live. The whole thing is built for coaches, course creators, agencies, and operators — not engineers.
Will my clients know they're talking to an AI?
Only if you want them to. Your FormWise AI is trained on your voice, your offer, and the way you actually communicate — so it sounds like a thoughtful team member, not a clunky chatbot. Most people can't tell.
Can I make it sound like me?
Yes. You can give your AI examples of how you write, the questions you usually ask new clients, the way you handle objections, and the language you use about your offer. The more you give it, the more it sounds like you wrote it.
What if I want to take over a conversation?
You're always in control. You can step in at any point, take over from your AI, or stop it from sending messages until you've reviewed them. Think of it as a teammate, not a replacement.
Is my client data safe?
Yes. Your Google BigQuery login and client information stay scoped to your workspace. We don't sell it, we don't share it, and we don't use your data to train anyone else's AI. You can disconnect Google BigQuery or delete everything any time.
What happens when Google BigQuery updates their app?
We handle it. When Google BigQuery adds new features or changes how something works, we update the integration in the background. You don't have to do anything — your AI just keeps working.
How fast can I actually get this running?
Most people are up and running the same day they sign up. Connecting Google BigQuery takes a few minutes. Teaching your AI to handle the work the way you'd want it done is the part worth slowing down for.
What is FormWise?
FormWise is the AI agent builder for coaches, course creators, and agencies. You connect the apps you already use — like Google BigQuery — train your AI on your offer and voice, and let it handle the work you've been doing manually: onboarding, follow-ups, support, admin. No code, no developers, no engineering team required.
Can I sell AI agents to my clients?
Yes. A lot of FormWise users build AI assistants and sell them as part of their offer — done-for-you AI setups, white-label assistants for client businesses, custom GPTs trained on a client's brand. You can charge a setup fee, a monthly retainer, or both.
Can I embed my AI on my website or in my course?
Yes. Every AI you build in FormWise can be embedded on your site, dropped into your course platform, or shared as a standalone link. Your clients and students just open it like any other web page — no app to download, no login hoops.
Do I need to know anything about AI to use this?
No. If you can describe what you want your AI to do in plain English — "greet new clients, ask these 3 questions, book them a call" — FormWise can build it. We handle the models, the prompts, the connections. You handle the part you already know: what your business actually needs.
About Google BigQuery on FormWise
Google BigQuery is a fully managed data warehouse for large-scale data analytics, offering fast SQL queries and machine learning capabilities on massive datasets
Connect Google BigQuery once and your FormWise AI gets 63 things it can do inside it. That means your AI can handle the Google BigQuery work in your business — the messages, the updates, the follow-ups, the admin — the way you would, just faster and around the clock.
You don't need to know how any of it works under the hood. We take care of keeping the connection alive, retrying if something fails, and making sure your data only ever moves where you tell it to.
New to Google BigQuery? Take a look at cloud.google.com/bigquery.
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Stop doing the Google BigQuery work yourself
Hand it off to an AI assistant that sounds like you, works around the clock, and never forgets a follow-up. Free to start.
