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Combine Google Cloud BigQuery data with Enrich Layer insights to build comprehensive customer profiles. Latenode's visual editor and affordable execution-based pricing simplifies complex data enrichment workflows and ensures scalability as your data grows.
Connect Google Cloud BigQuery and Enrich Layer in minutes with Latenode.
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Create a New Scenario to Connect Google Cloud BigQuery and Enrich Layer
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, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery or Enrich Layer will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or Enrich Layer, and select the appropriate trigger to start the scenario.
Add the Google Cloud BigQuery Node
Select the Google Cloud BigQuery node from the app selection panel on the right.
Google Cloud BigQuery
Configure the Google Cloud BigQuery
Click on the Google Cloud BigQuery node to configure it. You can modify the Google Cloud BigQuery URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Enrich Layer Node
Next, click the plus (+) icon on the Google Cloud BigQuery node, select Enrich Layer from the list of available apps, and choose the action you need from the list of nodes within Enrich Layer.
Google Cloud BigQuery
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Enrich Layer
Authenticate Enrich Layer
Now, click the Enrich Layer node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Enrich Layer settings. Authentication allows you to use Enrich Layer through Latenode.
Configure the Google Cloud BigQuery and Enrich Layer 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 and Enrich Layer Integration
Use various Latenode nodes to transform data and enhance your integration:
JavaScript
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AI Anthropic Claude 3
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Enrich Layer
Trigger on Webhook
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Google Cloud BigQuery
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring Google Cloud BigQuery, Enrich Layer, 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 and Enrich Layer integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Enrich Layer (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Google Cloud BigQuery + Enrich Layer + Salesforce: When new data is added to Google Cloud BigQuery, the contact or company information is enriched using Enrich Layer. The enriched data is then used to update the corresponding lead record in Salesforce, ensuring accurate and complete lead information.
HubSpot + Enrich Layer + Google Cloud BigQuery: When a new contact is created or updated in HubSpot, Enrich Layer is used to find and add firmographic data to the contact. The enriched contact data is then stored in Google Cloud BigQuery for analysis and reporting purposes.
About Google Cloud BigQuery
Use Google Cloud BigQuery in Latenode to automate data warehousing tasks. Query, analyze, and transform huge datasets as part of your workflows. Schedule data imports, trigger reports, or feed insights into other apps. Automate complex analysis without code and scale your insights with Latenode’s flexible, pay-as-you-go platform.
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About Enrich Layer
Enrich Layer inside Latenode automates data validation and enhancement. Fix errors and add missing info to leads or contacts. Clean up data from any source before it reaches your CRM or database. Latenode handles complex logic and scales the process without per-step costs, keeping data accurate and workflows efficient.
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How can I connect my Google Cloud BigQuery account to Enrich Layer using Latenode?
To connect your Google Cloud BigQuery account to Enrich Layer on Latenode, follow these steps:
Can I enrich BigQuery data with contextual firmographics?
Yes, using Latenode you can automatically enrich your BigQuery datasets with Enrich Layer. Benefit from seamless data transformations, no-code logic, and AI-powered data cleaning to get the most from your data.
What types of tasks can I perform by integrating Google Cloud BigQuery with Enrich Layer?
Integrating Google Cloud BigQuery with Enrich Layer allows you to perform various tasks, including:
How does Latenode handle large BigQuery datasets during enrichment?
Latenode efficiently processes large datasets by offering parallel execution and adjustable batch sizes, ensuring optimal performance without manual coding.
Are there any limitations to the Google Cloud BigQuery and Enrich Layer integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: