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

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

OCR Space
Configure the OCR Space
Click on the OCR Space node to configure it. You can modify the OCR Space 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 OCR Space 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 OCR Space 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 OCR Space 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 OCR Space, 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 OCR Space and Google Cloud BigQuery integration works as expected. Depending on your setup, data should flow between OCR Space 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 OCR Space and Google Cloud BigQuery
Google Drive + OCR Space + Google Sheets: When a new or modified file is detected in a Google Drive folder, the image is sent to OCR Space to convert it into text. The extracted text is then added as a new row in a Google Sheet.
Google Sheets + Google Drive + Google Sheets: When a new row is added to a Google Sheet, the automation finds a file in Google Drive. The data is then added as a comment to the Google sheet.
OCR Space and Google Cloud BigQuery integration alternatives
About OCR Space
Need to extract text from images or PDFs? Use OCR Space in Latenode to automatically process documents and integrate the data into your workflows. Automate invoice processing, data entry, or compliance checks. Latenode adds flexible logic, file parsing, and destinations to your OCR results, scaling beyond single-document processing.
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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 OCR Space and Google Cloud BigQuery
How can I connect my OCR Space account to Google Cloud BigQuery using Latenode?
To connect your OCR Space account to Google Cloud BigQuery on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select OCR Space and click on "Connect".
- Authenticate your OCR Space and Google Cloud BigQuery accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically analyze scanned invoices in BigQuery?
Yes, you can! Latenode simplifies this by automating data extraction from OCR Space to Google Cloud BigQuery, enabling advanced analytics and reporting, enhanced by no-code steps and custom JS code.
What types of tasks can I perform by integrating OCR Space with Google Cloud BigQuery?
Integrating OCR Space with Google Cloud BigQuery allows you to perform various tasks, including:
- Extract text from scanned documents and store it in BigQuery.
- Process image-based data into structured datasets for analysis.
- Automate invoice processing and data entry tasks.
- Build dashboards visualizing extracted data from OCR Space.
- Create audit trails of document processing using BigQuery logs.
How do I handle errors when OCR Space fails on Latenode?
Latenode's error handling lets you define fallback logic, retry mechanisms, or send alerts if OCR Space fails, ensuring data integrity.
Are there any limitations to the OCR Space and Google Cloud BigQuery integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large volumes of data may require optimizing workflow configurations.
- OCR Space API limits apply based on your OCR Space subscription.
- Complex document layouts may impact OCR accuracy, requiring pre-processing.