How to connect Google Cloud BigQuery (REST) and Deepgram
Create a New Scenario to Connect Google Cloud BigQuery (REST) and Deepgram
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 Deepgram will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or Deepgram, 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 Deepgram Node
Next, click the plus (+) icon on the Google Cloud BigQuery (REST) node, select Deepgram from the list of available apps, and choose the action you need from the list of nodes within Deepgram.

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Authenticate Deepgram
Now, click the Deepgram node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Deepgram settings. Authentication allows you to use Deepgram through Latenode.
Configure the Google Cloud BigQuery (REST) and Deepgram 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 Deepgram 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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AI Anthropic Claude 3
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Deepgram
Trigger on Webhook
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), Deepgram, 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 Deepgram integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Deepgram (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 Deepgram
Deepgram + Google Cloud BigQuery (REST) + Slack: This flow transcribes audio files from a URL using Deepgram, inserts the transcription data into a Google Cloud BigQuery table, and sends a summary of the transcription insights to a Slack channel.
Deepgram + Google Cloud BigQuery (REST) + Google Sheets: Transcribe customer support calls from a URL using Deepgram, insert the transcript into Google Cloud BigQuery, then insert aggregated findings into Google Sheets.
Google Cloud BigQuery (REST) and Deepgram 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 Deepgram
Need to transcribe audio/video inside your Latenode automations? Deepgram offers fast, accurate speech-to-text. Connect it to your workflows for automated meeting summaries, content analysis, or customer support monitoring. Fine-tune results with custom vocabularies, all within Latenode's visual interface and code blocks.
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See how Latenode works
FAQ Google Cloud BigQuery (REST) and Deepgram
How can I connect my Google Cloud BigQuery (REST) account to Deepgram using Latenode?
To connect your Google Cloud BigQuery (REST) account to Deepgram 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 Deepgram accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze call center audio stored in BigQuery via Deepgram?
Yes, you can! Latenode enables you to automatically send audio files from Google Cloud BigQuery (REST) to Deepgram for analysis. Get insights faster via low-code or custom code.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Deepgram?
Integrating Google Cloud BigQuery (REST) with Deepgram allows you to perform various tasks, including:
- Transcribing audio data stored within your Google Cloud BigQuery (REST) datasets.
- Analyzing sentiment from transcribed audio and storing results back in BigQuery.
- Automatically triggering alerts based on keywords identified by Deepgram.
- Generating reports from the combined audio transcription and analysis data.
- Classifying call reasons or customer issues from audio data automatically.
How does Latenode handle authentication for Google Cloud BigQuery (REST)?
Latenode uses secure OAuth to authenticate your Google Cloud BigQuery (REST) account, ensuring data privacy and security in your workflows.
Are there any limitations to the Google Cloud BigQuery (REST) and Deepgram integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large audio files may take significant time to process depending on Deepgram's API load.
- Rate limits on either Google Cloud BigQuery (REST) or Deepgram's API may affect workflow speed.
- Complex data transformations might require custom JavaScript nodes for optimal performance.