How to connect Google Cloud BigQuery (REST) and Monster API
Create a New Scenario to Connect Google Cloud BigQuery (REST) and Monster API
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 Monster API will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or Monster API, 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 Monster API Node
Next, click the plus (+) icon on the Google Cloud BigQuery (REST) node, select Monster API from the list of available apps, and choose the action you need from the list of nodes within Monster API.

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Monster API

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

Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), Monster API, 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 Monster API integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Monster API (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 Monster API
Monster API + Google Cloud BigQuery (REST) + Slack: Automatically fetch job posting data from the Monster API, analyze the data using Google Cloud BigQuery by creating a query job, and then post key findings and potential skills gaps to a designated Slack channel to alert recruiters.
Monster API + Google Cloud BigQuery (REST) + Google Sheets: Track job posting performance data by periodically fetching results from the Monster API, inserting the data into a BigQuery table, then querying BigQuery for summarized posting metrics and updating a Google Sheet to present a clear performance report.
Google Cloud BigQuery (REST) and Monster API 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 Monster API
Struggling with unreliable or slow data? Integrate Monster API in Latenode to build automated data validation and cleansing workflows. Use its data enrichment and verification features to refine your data, then route the cleaned info to other services. Benefit from Latenode's visual editor and scalability for consistent, error-free data flow.
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See how Latenode works
FAQ Google Cloud BigQuery (REST) and Monster API
How can I connect my Google Cloud BigQuery (REST) account to Monster API using Latenode?
To connect your Google Cloud BigQuery (REST) account to Monster API 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 Monster API accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I enrich Monster API data with BigQuery insights?
Yes, you can easily enrich your Monster API data using Google Cloud BigQuery (REST) in Latenode. Leverage BigQuery's analytics in your workflows for deeper insights and enhanced data-driven decisions.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Monster API?
Integrating Google Cloud BigQuery (REST) with Monster API allows you to perform various tasks, including:
- Storing Monster API data into a Google Cloud BigQuery (REST) data warehouse.
- Analyzing job market trends using BigQuery and Monster API job postings.
- Creating custom reports combining job data with internal company metrics.
- Triggering alerts in Monster API based on BigQuery data analysis results.
- Automating data updates between Monster API and BigQuery on a schedule.
Can I use server-side JavaScript with BigQuery(REST) in Latenode?
Yes, Latenode supports server-side JavaScript code. Use it to implement advanced Google Cloud BigQuery (REST) logic or data transformation tasks.
Are there any limitations to the Google Cloud BigQuery (REST) and Monster API integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by Google Cloud BigQuery (REST) and Monster API still apply.
- Complex data transformations may require server-side JavaScript knowledge.
- Initial setup requires familiarity with Google Cloud BigQuery (REST) authentication.