Google Cloud BigQuery (REST) and ConvertAPI Integration

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Automatically convert and archive reports from Google Cloud BigQuery (REST) into accessible formats using ConvertAPI. Latenode's visual editor and affordable, execution-based pricing simplify complex data workflows. Easily customize formats and automate archival processes with built-in no-code tools.

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Google Cloud BigQuery (REST)

ConvertAPI

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Cloud BigQuery (REST) and ConvertAPI

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

In the workspace, click the β€œCreate 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 ConvertAPI will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or ConvertAPI, 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.

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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.

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Add the ConvertAPI Node

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

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Authenticate ConvertAPI

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

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Configure the Google Cloud BigQuery (REST) and ConvertAPI 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 (REST) and ConvertAPI 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 (REST), ConvertAPI, 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 β€œRun once” and triggering an event to check if the Google Cloud BigQuery (REST) and ConvertAPI integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and ConvertAPI (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 ConvertAPI

Google Cloud BigQuery (REST) + ConvertAPI + Slack: This automation flow starts by querying data from Google Cloud BigQuery. The retrieved data is then converted into a PDF report using ConvertAPI. Finally, the generated PDF report is sent to a designated Slack channel.

ConvertAPI + Google Cloud BigQuery (REST) + Google Drive: This flow converts a document using ConvertAPI. The metadata of the converted document, like file name and type, is then stored in Google Cloud BigQuery. Finally, the converted file is saved to a specified folder in Google Drive.

Google Cloud BigQuery (REST) and ConvertAPI 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.

About ConvertAPI

Automate file conversions within Latenode. ConvertAPI handles PDFs, images, documents, and more. Instead of manual uploads or custom code, build automated workflows to convert files as they arrive, then parse data or trigger follow-up actions. Scales easily, no coding needed.

Google Cloud BigQuery (REST) + ConvertAPI integration

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FAQ Google Cloud BigQuery (REST) and ConvertAPI

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

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

Can I convert BigQuery data to PDF using ConvertAPI?

Yes, you can! Latenode lets you automate this. Extract data from Google Cloud BigQuery (REST), pass it to ConvertAPI, and automatically generate PDFs for reporting, archiving, or sharing β€” all without coding.

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

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

  • Automating report generation from database queries into shareable PDFs.
  • Converting query results to various document formats for wider accessibility.
  • Creating dynamic invoices from database records and sending them automatically.
  • Generating visual dashboards by converting data into charts and PDFs.
  • Archiving database snapshots as standardized, searchable PDF documents.

How does Latenode handle large datasets from Google Cloud BigQuery (REST)?

Latenode processes large datasets efficiently, streaming data to ConvertAPI for conversion. This prevents memory issues and ensures scalable automation.

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

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

  • Complex formatting may require custom JavaScript for data transformation.
  • Very large datasets might require optimized queries for efficient processing.
  • ConvertAPI usage is subject to their API rate limits and pricing tiers.

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