Google Cloud BigQuery and OCR Space Integration

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Extract data from documents with OCR Space, then analyze it in Google Cloud BigQuery. Latenode's visual editor simplifies the integration, and affordable execution-based pricing makes scaling data workflows easy.

Swap Apps

Google Cloud BigQuery

OCR Space

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Cloud BigQuery and OCR Space

Create a New Scenario to Connect Google Cloud BigQuery and OCR Space

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 OCR Space will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or OCR Space, 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.

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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.

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Add the OCR Space Node

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

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Authenticate OCR Space

Now, click the OCR Space node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your OCR Space settings. Authentication allows you to use OCR Space through Latenode.

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Configure the Google Cloud BigQuery and OCR Space 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 BigQuery and OCR Space 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 BigQuery, OCR Space, 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 OCR Space integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and OCR Space (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 OCR Space

OCR Space + Google Cloud BigQuery + Google Sheets: When a new image is uploaded, OCR Space extracts the text from the image. This data is then stored in Google Cloud BigQuery. Finally, a summary of the extracted data is added to a Google Sheet.

OCR Space + Google Cloud BigQuery + Slack: When a new image is processed by OCR Space, the extracted text data is stored in Google Cloud BigQuery. Then, a summary of the processed document is sent to a specified Slack channel for review.

Google Cloud BigQuery and OCR Space 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.

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.

See how Latenode works

FAQ Google Cloud BigQuery and OCR Space

How can I connect my Google Cloud BigQuery account to OCR Space using Latenode?

To connect your Google Cloud BigQuery account to OCR Space 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 OCR Space accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automate data extraction and analysis from scanned documents?

Yes, you can! Latenode simplifies this by automating data transfer. Extract text with OCR Space, then load it into Google Cloud BigQuery for analysis—all without code.

What types of tasks can I perform by integrating Google Cloud BigQuery with OCR Space?

Integrating Google Cloud BigQuery with OCR Space allows you to perform various tasks, including:

  • Automatically extracting data from invoices and storing it in BigQuery.
  • Processing scanned contracts and analyzing key terms using BigQuery.
  • Analyzing data from image-based reports using OCR and BigQuery.
  • Ingesting data from PDFs into Google Cloud BigQuery for sentiment analysis.
  • Creating dashboards from scanned documents using OCR Space and BigQuery.

Can I use JavaScript to transform data before loading to BigQuery?

Yes, using Latenode's JavaScript blocks, you can preprocess OCR Space data before it's sent to Google Cloud BigQuery for optimal analysis.

Are there any limitations to the Google Cloud BigQuery and OCR Space integration on Latenode?

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

  • Large volumes of OCR requests may impact OCR Space API rate limits.
  • Complex document layouts can sometimes reduce OCR accuracy.
  • Google Cloud BigQuery costs may increase with large data processing jobs.

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