How to connect Google Cloud BigQuery (REST) and OpenAI GPT Assistants
Create a New Scenario to Connect Google Cloud BigQuery (REST) and OpenAI GPT Assistants
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud BigQuery (REST), triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery (REST) or OpenAI GPT Assistants will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or OpenAI GPT Assistants, and select the appropriate trigger to start the scenario.

Add the Google Cloud BigQuery (REST) Node
Select the Google Cloud BigQuery (REST) node from the app selection panel on the right.

Google Cloud BigQuery (REST)
Configure the Google Cloud BigQuery (REST)
Click on the Google Cloud BigQuery (REST) node to configure it. You can modify the Google Cloud BigQuery (REST) URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the OpenAI GPT Assistants Node
Next, click the plus (+) icon on the Google Cloud BigQuery (REST) node, select OpenAI GPT Assistants from the list of available apps, and choose the action you need from the list of nodes within OpenAI GPT Assistants.

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OpenAI GPT Assistants
Authenticate OpenAI GPT Assistants
Now, click the OpenAI GPT Assistants node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your OpenAI GPT Assistants settings. Authentication allows you to use OpenAI GPT Assistants through Latenode.
Configure the Google Cloud BigQuery (REST) and OpenAI GPT Assistants Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Cloud BigQuery (REST) and OpenAI GPT Assistants Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), OpenAI GPT Assistants, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud BigQuery (REST) and OpenAI GPT Assistants integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and OpenAI GPT Assistants (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud BigQuery (REST) and OpenAI GPT Assistants
Google Cloud BigQuery (REST) + OpenAI GPT Assistants + Slack: Executes a BigQuery query to analyze data, then uses a GPT Assistant to summarize the findings, and finally shares the summary in a designated Slack channel.
Google Sheets + OpenAI GPT Assistants + Google Cloud BigQuery (REST): When new feedback is added to Google Sheets, a GPT Assistant analyzes the sentiment and stores the results in a BigQuery table for further trend analysis.
Google Cloud BigQuery (REST) and OpenAI GPT Assistants integration alternatives
About Google Cloud BigQuery (REST)
Automate BigQuery data workflows in Latenode. Query and analyze massive datasets directly within your automation scenarios, bypassing manual SQL. Schedule queries, transform results with JavaScript, and pipe data to other apps. Scale your data processing without complex coding or expensive per-operation fees. Perfect for reporting, analytics, and data warehousing automation.
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About OpenAI GPT Assistants
Use OpenAI GPT Assistants within Latenode to automate complex tasks like customer support or content creation. Configure Assistants with prompts and integrate them into broader workflows. Chain them with file parsing, webhooks, or database updates for scalable, automated solutions. Benefit from Latenode's no-code flexibility and affordable execution-based pricing.
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FAQ Google Cloud BigQuery (REST) and OpenAI GPT Assistants
How can I connect my Google Cloud BigQuery (REST) account to OpenAI GPT Assistants using Latenode?
To connect your Google Cloud BigQuery (REST) account to OpenAI GPT Assistants on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery (REST) and click on "Connect".
- Authenticate your Google Cloud BigQuery (REST) and OpenAI GPT Assistants accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically analyze BigQuery data with an AI assistant?
Yes, you can! Latenode automates data analysis using AI. Connect BigQuery data to OpenAI to gain faster, smarter insights—no coding required, plus you get scalable performance.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with OpenAI GPT Assistants?
Integrating Google Cloud BigQuery (REST) with OpenAI GPT Assistants allows you to perform various tasks, including:
- Generate summaries of large datasets stored in Google Cloud BigQuery.
- Automatically categorize and tag customer feedback from BigQuery datasets.
- Create personalized reports using data queried from Google Cloud BigQuery.
- Build AI-powered chatbots that use BigQuery data for informed responses.
- Automate data cleaning and transformation processes via AI instructions.
Can I use custom SQL queries to filter data before sending it to OpenAI?
Yes, Latenode supports custom SQL queries within the BigQuery integration. This lets you filter and process data before AI analysis, optimizing performance.
Are there any limitations to the Google Cloud BigQuery (REST) and OpenAI GPT Assistants integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by the Google Cloud BigQuery (REST) and OpenAI GPT Assistants APIs still apply.
- Complex data transformations might require custom JavaScript code.
- The integration is limited by the context window of the OpenAI GPT Assistants model.