OCR Space and Microsoft SQL Server Integration

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Automatically extract text from images using OCR Space, then store and manage the data in Microsoft SQL Server. Latenode's visual editor makes this complex data pipeline simple to build and our affordable pricing lets you scale the automation without breaking the bank.

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OCR Space

Microsoft SQL Server

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect OCR Space and Microsoft SQL Server

Create a New Scenario to Connect OCR Space and Microsoft SQL Server

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 Microsoft SQL Server will be your first step. To do this, click "Choose an app," find OCR Space or Microsoft SQL Server, 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.

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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.

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Add the Microsoft SQL Server Node

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

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Authenticate Microsoft SQL Server

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

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Configure the OCR Space and Microsoft SQL Server 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 OCR Space and Microsoft SQL Server 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 OCR Space, Microsoft SQL Server, 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 Microsoft SQL Server integration works as expected. Depending on your setup, data should flow between OCR Space and Microsoft SQL Server (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 Microsoft SQL Server

OCR Space + Microsoft SQL Server + Slack: When a new image is available, OCR Space extracts the text. The extracted text is then inserted as a new row into a Microsoft SQL Server database. Finally, a notification is sent via Slack to the accounting team.

Microsoft SQL Server + OCR Space + Google Sheets: When a new or updated row is available in Microsoft SQL Server, the data can be synced to Google Sheets. If the row contains a link to an image, OCR Space can convert the image to text and append it to the row.

OCR Space and Microsoft SQL Server 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.

About Microsoft SQL Server

Use Microsoft SQL Server in Latenode to automate database tasks. Directly query, update, or insert data in response to triggers. Sync SQL data with other apps; simplify data pipelines for reporting and analytics. Build automated workflows without complex coding to manage databases efficiently and scale operations.

See how Latenode works

FAQ OCR Space and Microsoft SQL Server

How can I connect my OCR Space account to Microsoft SQL Server using Latenode?

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

Can I automate invoice data extraction and storage?

Yes, you can! Latenode's visual editor simplifies this. Automatically extract data from invoices using OCR Space, then store it securely in Microsoft SQL Server. Benefit from robust data management and streamlined processes.

What types of tasks can I perform by integrating OCR Space with Microsoft SQL Server?

Integrating OCR Space with Microsoft SQL Server allows you to perform various tasks, including:

  • Automating data entry from scanned documents directly into a database.
  • Creating searchable archives of physical documents using OCR and database storage.
  • Extracting data from receipts and logging expenses automatically.
  • Processing scanned forms and updating customer records in real-time.
  • Validating extracted data against database entries for quality control.

How does Latenode handle large volumes of OCR Space data?

Latenode scales to handle substantial OCR Space data. Process large files, manage data pipelines, and ensure efficient transfers to Microsoft SQL Server.

Are there any limitations to the OCR Space and Microsoft SQL Server integration on Latenode?

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

  • OCR Space API usage is subject to their rate limits, which may affect processing speed.
  • Complex document layouts may require advanced OCR Space configurations for optimal accuracy.
  • Data transformation between OCR Space and Microsoft SQL Server may require custom JavaScript code.

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