Google Cloud Speech-To-Text and Google Cloud BigQuery (REST) Integration

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Transcribe audio using Google Cloud Speech-To-Text, then analyze the data in Google Cloud BigQuery (REST). Latenode’s visual editor makes it easy, and affordable pricing lets you scale transcript analysis without breaking the bank.

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Google Cloud Speech-To-Text

Google Cloud BigQuery (REST)

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Cloud Speech-To-Text and Google Cloud BigQuery (REST)

Create a New Scenario to Connect Google Cloud Speech-To-Text and Google Cloud BigQuery (REST)

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

Add the Google Cloud Speech-To-Text Node

Select the Google Cloud Speech-To-Text node from the app selection panel on the right.

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Configure the Google Cloud Speech-To-Text

Click on the Google Cloud Speech-To-Text node to configure it. You can modify the Google Cloud Speech-To-Text URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Add the Google Cloud BigQuery (REST) Node

Next, click the plus (+) icon on the Google Cloud Speech-To-Text node, select Google Cloud BigQuery (REST) from the list of available apps, and choose the action you need from the list of nodes within Google Cloud BigQuery (REST).

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Authenticate Google Cloud BigQuery (REST)

Now, click the Google Cloud BigQuery (REST) node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud BigQuery (REST) settings. Authentication allows you to use Google Cloud BigQuery (REST) through Latenode.

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Configure the Google Cloud Speech-To-Text and Google Cloud BigQuery (REST) Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Set Up the Google Cloud Speech-To-Text and Google Cloud BigQuery (REST) 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 Speech-To-Text, Google Cloud BigQuery (REST), 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 Speech-To-Text and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Google Cloud Speech-To-Text and Google Cloud BigQuery (REST) (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 Speech-To-Text and Google Cloud BigQuery (REST)

Google Cloud Speech-To-Text + Google Cloud BigQuery (REST) + Slack: This automation transcribes audio files stored in Google Cloud Storage using Google Cloud Speech-To-Text. The transcribed text is then stored in Google Cloud BigQuery. Finally, a Slack message is sent to a specified channel when new transcriptions are added to BigQuery.

Google Cloud BigQuery (REST) + Google Cloud Speech-To-Text + Google Sheets: This flow analyzes transcribed audio data stored in Google Cloud BigQuery. The data is queried, and the results are used by Google Cloud Speech-To-Text for further analysis (potentially summarization or keyword extraction - utilizing the 'Recognize Speech' action to analyze sections of the existing transcript). The analysis findings are then logged into a Google Sheet for review and tracking.

Google Cloud Speech-To-Text and Google Cloud BigQuery (REST) integration alternatives

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.

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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FAQ Google Cloud Speech-To-Text and Google Cloud BigQuery (REST)

How can I connect my Google Cloud Speech-To-Text account to Google Cloud BigQuery (REST) using Latenode?

To connect your Google Cloud Speech-To-Text account to Google Cloud BigQuery (REST) on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Google Cloud Speech-To-Text and click on "Connect".
  • Authenticate your Google Cloud Speech-To-Text and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I analyze call center audio?

Yes, you can. Latenode's visual editor simplifies data transformations from audio to structured insights. This automates analysis and improves response strategies.

What types of tasks can I perform by integrating Google Cloud Speech-To-Text with Google Cloud BigQuery (REST)?

Integrating Google Cloud Speech-To-Text with Google Cloud BigQuery (REST) allows you to perform various tasks, including:

  • Transcribing audio and storing results in structured tables.
  • Performing sentiment analysis on transcribed speech data.
  • Generating reports on frequently mentioned keywords.
  • Automatically updating dashboards with real-time insights.
  • Archiving and indexing transcribed audio data.

How does Latenode handle Google Cloud Speech-To-Text authentication?

Latenode provides secure and straightforward OAuth-based authentication, allowing you to easily authorize your Google Cloud Speech-To-Text account.

Are there any limitations to the Google Cloud Speech-To-Text and Google Cloud BigQuery (REST) integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Large audio files may require significant processing time.
  • BigQuery costs depend on your data volume and query complexity.
  • Real-time transcription has inherent latency.

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