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

Add the Cloudinary Node
Select the Cloudinary node from the app selection panel on the right.


Cloudinary

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


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Authenticate Google Cloud BigQuery
Now, click the Google Cloud BigQuery 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 settings. Authentication allows you to use Google Cloud BigQuery through Latenode.
Configure the Cloudinary and Google Cloud BigQuery 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 Cloudinary and Google Cloud BigQuery 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring Cloudinary, Google Cloud BigQuery, 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 Cloudinary and Google Cloud BigQuery integration works as expected. Depending on your setup, data should flow between Cloudinary and Google Cloud BigQuery (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Cloudinary and Google Cloud BigQuery
Cloudinary + Google Sheets: When a new resource is uploaded to Cloudinary, its details are added as a new row in a Google Sheet, enabling performance tracking and trend visualization.
Cloudinary + Google Sheets + Slack: When a new resource is uploaded to Cloudinary, its details are added as a new row in a Google Sheet. When new data is added to the Google Sheet, a summary notification is sent to a Slack channel.
Cloudinary and Google Cloud BigQuery integration alternatives

About Cloudinary
Automate image and video optimization with Cloudinary in Latenode. Resize, convert, and deliver media assets based on triggers or data from any app. Streamline content workflows by integrating Cloudinary’s powerful transformations directly into your automated processes, reducing manual work. Scale efficiently and pay only for execution time.
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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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See how Latenode works
FAQ Cloudinary and Google Cloud BigQuery
How can I connect my Cloudinary account to Google Cloud BigQuery using Latenode?
To connect your Cloudinary account to Google Cloud BigQuery on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Cloudinary and click on "Connect".
- Authenticate your Cloudinary and Google Cloud BigQuery accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze image performance metrics from Cloudinary in BigQuery?
Yes, easily! Latenode automates data transfer from Cloudinary to BigQuery. Analyze image views, conversions, and more to optimize your visual content strategy using advanced SQL queries.
What types of tasks can I perform by integrating Cloudinary with Google Cloud BigQuery?
Integrating Cloudinary with Google Cloud BigQuery allows you to perform various tasks, including:
- Backing up Cloudinary asset metadata to a secure BigQuery dataset.
- Creating reports on the most popular image formats and sizes.
- Analyzing the geographic distribution of image views.
- Tracking the performance of different Cloudinary transformations.
- Calculating the total storage usage across all Cloudinary assets.
What kind of transformations can I trigger on Cloudinary via Latenode?
Latenode allows you to automate any Cloudinary transformation—resizing, cropping, watermarking—based on events or data changes from other apps.
Are there any limitations to the Cloudinary and Google Cloud BigQuery integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data synchronization may take time depending on data volume.
- Complex transformations may require JavaScript for advanced customization.
- BigQuery costs may apply based on your data storage and query usage.