How to connect Google Cloud BigQuery and Google Cloud Speech-To-Text
Create a New Scenario to Connect Google Cloud BigQuery and Google Cloud Speech-To-Text
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, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery or Google Cloud Speech-To-Text will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or Google Cloud Speech-To-Text, and select the appropriate trigger to start the scenario.

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

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

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Authenticate Google Cloud Speech-To-Text
Now, click the Google Cloud Speech-To-Text node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud Speech-To-Text settings. Authentication allows you to use Google Cloud Speech-To-Text through Latenode.
Configure the Google Cloud BigQuery and Google Cloud Speech-To-Text 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 and Google Cloud Speech-To-Text 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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Google Cloud Speech-To-Text
Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud BigQuery, Google Cloud Speech-To-Text, 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 and Google Cloud Speech-To-Text integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Google Cloud Speech-To-Text (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 and Google Cloud Speech-To-Text
Google Cloud Speech-To-Text + Google Cloud BigQuery + Slack: Transcribe audio from customer service calls using Google Cloud Speech-To-Text. Store the transcripts in Google Cloud BigQuery, then post a summary of the transcription results to a designated Slack channel.
Google Cloud Speech-To-Text + Google Cloud BigQuery + Google Sheets: Transcribe meeting audio with Google Cloud Speech-To-Text, store the transcripts in Google Cloud BigQuery, and then extract and list action items in a Google Sheet.
Google Cloud BigQuery and Google Cloud Speech-To-Text integration alternatives
About Google Cloud BigQuery
Use Google Cloud BigQuery in Latenode to automate data warehousing tasks. Query, analyze, and transform huge datasets as part of your workflows. Schedule data imports, trigger reports, or feed insights into other apps. Automate complex analysis without code and scale your insights with Latenode’s flexible, pay-as-you-go platform.
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About Google Cloud Speech-To-Text
Automate audio transcription using Google Cloud Speech-To-Text within Latenode. Convert audio files to text and use the results to populate databases, trigger alerts, or analyze customer feedback. Latenode provides visual tools to manage the flow, plus code options for custom parsing or filtering. Scale voice workflows without complex coding.
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See how Latenode works
FAQ Google Cloud BigQuery and Google Cloud Speech-To-Text
How can I connect my Google Cloud BigQuery account to Google Cloud Speech-To-Text using Latenode?
To connect your Google Cloud BigQuery account to Google Cloud Speech-To-Text on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery and click on "Connect".
- Authenticate your Google Cloud BigQuery and Google Cloud Speech-To-Text accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze call center audio and store insights?
Yes, you can. Latenode allows seamless data transformations and scheduled runs. Benefit from analyzing audio, deriving insights, and storing them in BigQuery effortlessly.
What types of tasks can I perform by integrating Google Cloud BigQuery with Google Cloud Speech-To-Text?
Integrating Google Cloud BigQuery with Google Cloud Speech-To-Text allows you to perform various tasks, including:
- Transcribing audio files and storing the text in a BigQuery dataset.
- Analyzing customer service call transcripts for sentiment trends.
- Creating searchable archives of spoken content stored in BigQuery.
- Generating reports from transcribed audio data within BigQuery.
- Automating data extraction from speech for business intelligence.
How secure is my Google Cloud BigQuery data when using Latenode?
Latenode uses secure authentication protocols. Your Google Cloud BigQuery data remains secure, leveraging Google Cloud's existing security measures.
Are there any limitations to the Google Cloud BigQuery and Google Cloud Speech-To-Text integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large audio files may require significant processing time.
- The accuracy of speech-to-text depends on audio quality.
- Data transfer costs are subject to Google Cloud's pricing.