Google Ads and Google Cloud BigQuery Integration

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Google Ads

Google Cloud BigQuery

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Ads and Google Cloud BigQuery

Create a New Scenario to Connect Google Ads and Google Cloud BigQuery

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

Add the Google Ads Node

Select the Google Ads node from the app selection panel on the right.

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Configure the Google Ads

Click on the Google Ads node to configure it. You can modify the Google Ads 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 Node

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

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Authenticate Google Cloud BigQuery

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

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

Most powerful ways to connect Google Ads and Google Cloud BigQuery

Google Ads + Google Cloud BigQuery + Google Sheets: Tracks ad spend and performance from Google Ads, storing the data in Google Cloud BigQuery. Then, generates a weekly report in Google Sheets summarizing the key metrics.

Google Cloud BigQuery + Google Ads + Slack: When BigQuery detects unusual ad spend patterns based on a query, a notification is sent to the marketing team via Slack to investigate the anomaly.

Google Ads and Google Cloud BigQuery integration alternatives

About Google Ads

Use Google Ads in Latenode to automate campaign management and reporting. Pull ad performance data, adjust bids based on real-time events, or trigger alerts for budget changes. Combine with other apps to build custom marketing workflows. Latenode's flexibility avoids rigid, pre-built integrations and costly per-step pricing.

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.

See how Latenode works

FAQ Google Ads and Google Cloud BigQuery

How can I connect my Google Ads account to Google Cloud BigQuery using Latenode?

To connect your Google Ads account to Google Cloud BigQuery on Latenode, follow these steps:

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

Can I automate custom report generation?

Yes, you can! Latenode's visual editor and JavaScript blocks allow building advanced report automation, significantly improving efficiency compared to manual data handling.

What types of tasks can I perform by integrating Google Ads with Google Cloud BigQuery?

Integrating Google Ads with Google Cloud BigQuery allows you to perform various tasks, including:

  • Automating data transfers for ad performance analysis.
  • Building custom dashboards with combined datasets.
  • Scheduling regular backups of your Google Ads data.
  • Creating alerts based on campaign performance metrics.
  • Enriching ad data with external sources for better insights.

Can I use JavaScript for enhanced data transformation?

Yes! Latenode’s JavaScript blocks let you transform data between Google Ads and BigQuery, enabling complex calculations and custom logic.

Are there any limitations to the Google Ads and Google Cloud BigQuery integration on Latenode?

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

  • Data transfer speeds depend on the size of the dataset.
  • API rate limits for Google Ads and BigQuery apply.
  • Complex transformations may require JavaScript coding.

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