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

Add the Google Cloud BigQuery (REST) Node
Select the Google Cloud BigQuery (REST) node from the app selection panel on the right.

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

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Authenticate Docparser
Now, click the Docparser node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Docparser settings. Authentication allows you to use Docparser through Latenode.
Configure the Google Cloud BigQuery (REST) and Docparser 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 Google Cloud BigQuery (REST) and Docparser 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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AI Anthropic Claude 3
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Trigger on Webhook
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), Docparser, 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 (REST) and Docparser integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Docparser (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 (REST) and Docparser
Docparser + Google Sheets + Google Sheets: When a document is parsed in Docparser, the extracted data is added as a new row in a Google Sheet. This new row addition then triggers an update to another Google Sheet, potentially for summary or reporting purposes.
Docparser + Google Cloud BigQuery + Slack: After Docparser extracts data from a document, the data is loaded into Google Cloud BigQuery. A Slack message is then sent to a specified channel to notify the team about the new data entry.
Google Cloud BigQuery (REST) and Docparser integration alternatives
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.
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About Docparser
Extract data from PDFs, invoices, and forms automatically with Docparser in Latenode. Stop manual data entry. Build workflows that trigger actions based on parsed content. Use Latenode’s no-code tools to filter, transform, and route data to your database or apps, creating scalable document processing pipelines.
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FAQ Google Cloud BigQuery (REST) and Docparser
How can I connect my Google Cloud BigQuery (REST) account to Docparser using Latenode?
To connect your Google Cloud BigQuery (REST) account to Docparser on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery (REST) and click on "Connect".
- Authenticate your Google Cloud BigQuery (REST) and Docparser accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze parsed invoice data in BigQuery?
Yes, you can! Latenode allows automated data transfer from Docparser to Google Cloud BigQuery (REST) for analysis. Leverage BigQuery's power to identify trends in invoice data.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Docparser?
Integrating Google Cloud BigQuery (REST) with Docparser allows you to perform various tasks, including:
- Automatically exporting parsed data from Docparser into Google Cloud BigQuery (REST).
- Creating real-time dashboards with parsed data using BigQuery and visualization tools.
- Building custom reports using SQL queries on Docparser data within BigQuery.
- Scheduling regular imports of updated Docparser data into your BigQuery datasets.
- Enriching existing BigQuery data with information extracted from documents via Docparser.
How do I handle authentication for Google Cloud BigQuery (REST) in Latenode?
Latenode uses secure OAuth 2.0 for Google Cloud BigQuery (REST), simplifying authentication and protecting your credentials effectively.
Are there any limitations to the Google Cloud BigQuery (REST) and Docparser integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large document parsing may impact workflow execution speed depending on Docparser's API limits.
- Complex data transformations might require JavaScript blocks for customized data mapping.
- Initial setup requires familiarity with both Google Cloud BigQuery (REST) and Docparser API structures.