Airparser and Google Cloud BigQuery (REST) Integration

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Automatically send parsed data from Airparser to Google Cloud BigQuery (REST) for analysis. Latenode’s visual editor makes setup simple, while affordable execution-based pricing supports even the most demanding data workflows.

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Airparser

Google Cloud BigQuery (REST)

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Airparser and Google Cloud BigQuery (REST)

Create a New Scenario to Connect Airparser and Google Cloud BigQuery (REST)

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

Add the Airparser Node

Select the Airparser node from the app selection panel on the right.

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Airparser

Configure the Airparser

Click on the Airparser node to configure it. You can modify the Airparser URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Run node once

Add the Google Cloud BigQuery (REST) Node

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

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Authenticate Google Cloud BigQuery (REST)

Now, click the Google Cloud BigQuery (REST) 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 (REST) settings. Authentication allows you to use Google Cloud BigQuery (REST) through Latenode.

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Configure the Airparser and Google Cloud BigQuery (REST) 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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Run node once

Set Up the Airparser and Google Cloud BigQuery (REST) 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 Airparser, Google Cloud BigQuery (REST), 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 Airparser and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Airparser and Google Cloud BigQuery (REST) (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Airparser and Google Cloud BigQuery (REST)

Airparser + Google Cloud BigQuery (REST) + Google Sheets: When a new document is uploaded to Airparser, the data is extracted and inserted into a BigQuery table. A summary of the data is then added as a new row to a Google Sheet.

Google Cloud BigQuery (REST) + Airparser + Slack: When a new row is added to a BigQuery table containing customer support requests, Airparser analyzes the text for urgency. If urgent, a notification is sent to the support team on Slack.

Airparser and Google Cloud BigQuery (REST) integration alternatives

About Airparser

Airparser in Latenode extracts data from PDFs, emails, and documents. Automate data entry by feeding parsed content directly into your CRM or database. Use Latenode's logic functions to validate or transform data, then trigger actions like sending notifications or updating records. Scale document processing without complex code.

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.

See how Latenode works

FAQ Airparser and Google Cloud BigQuery (REST)

How can I connect my Airparser account to Google Cloud BigQuery (REST) using Latenode?

To connect your Airparser account to Google Cloud BigQuery (REST) on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Airparser and click on "Connect".
  • Authenticate your Airparser and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I archive parsed documents to BigQuery automatically?

Yes, you can! Latenode automates data flow from Airparser to Google Cloud BigQuery (REST), creating a scalable archive. Analyze large datasets and gain insights without manual data transfers.

What types of tasks can I perform by integrating Airparser with Google Cloud BigQuery (REST)?

Integrating Airparser with Google Cloud BigQuery (REST) allows you to perform various tasks, including:

  • Archive parsed data for long-term storage and compliance.
  • Analyze document trends and extract key business insights.
  • Visualize parsed data using BigQuery's BI integrations.
  • Create automated reports based on parsed document content.
  • Enrich existing BigQuery datasets with data from documents.

How do I handle errors when parsing documents in Latenode?

Latenode's error handling provides real-time alerts and retry logic. Use JavaScript blocks for custom error processing and maintain data integrity.

Are there any limitations to the Airparser and Google Cloud BigQuery (REST) integration on Latenode?

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

  • BigQuery quotas and limits still apply when writing data.
  • Complex data transformations may require JavaScript coding.
  • Airparser API limits affect the frequency of data extraction.

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