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

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Authenticate Miro
Now, click the Miro node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Miro settings. Authentication allows you to use Miro through Latenode.
Configure the Google Cloud BigQuery (REST) and Miro 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 Miro 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), Miro, 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 Miro integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Miro (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 Miro
Google Cloud BigQuery (REST) + Miro + Slack: A query job is created and its results retrieved from BigQuery. A new board is created on Miro, populated with the data, and the board's link is then sent to a specified Slack channel.
Miro + Google Cloud BigQuery (REST) + Jira: When a Miro board is updated, a new query job is created in BigQuery to analyze relevant data, and a Jira issue is created to track the progress of the analysis.
Google Cloud BigQuery (REST) and Miro 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 Miro
Automate Miro board updates based on triggers from other apps. Latenode connects Miro to your workflows, enabling automatic creation of cards, text, or frames. Update Miro based on data from CRMs, databases, or project management tools, reducing manual work. Perfect for agile project tracking and visual process management, inside fully automated scenarios.
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FAQ Google Cloud BigQuery (REST) and Miro
How can I connect my Google Cloud BigQuery (REST) account to Miro using Latenode?
To connect your Google Cloud BigQuery (REST) account to Miro 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 Miro accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically update Miro boards with BigQuery data?
Yes, with Latenode you can! Automatically update Miro boards with real-time data insights from Google Cloud BigQuery (REST), keeping teams aligned and informed with dynamic visualisations.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Miro?
Integrating Google Cloud BigQuery (REST) with Miro allows you to perform various tasks, including:
- Visualize database query results directly on Miro boards.
- Create reports with live metrics for collaborative analysis.
- Automate data-driven decisions within project workflows.
- Generate Miro mind maps based on BigQuery data relationships.
- Update product roadmaps with real-time usage data.
How secure is the Google Cloud BigQuery (REST) connection on Latenode?
Latenode employs advanced encryption and security protocols to ensure secure data transfer between Google Cloud BigQuery (REST) and your workflows.
Are there any limitations to the Google Cloud BigQuery (REST) and Miro integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large data transfers from BigQuery may impact workflow speed.
- Complex BigQuery queries require optimized Latenode configurations.
- Miro API rate limits may affect high-volume data updates.