The article guides you through setting up the Google Ads → Google BigQuery pipeline to seamlessly receive daily cost data within the schema. Follow the steps below to get started.
Getting Started Requirements
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Access to Google Ads account:
- Ensure your Google account has one of these access levels in the Google Ads account: 'Read only', 'Standard', or 'Admin'. If it doesn't have access, then contact the administrator of your Google Ads account. Learn more
-
Google Cloud Platform (GCP) setup:
- Use the Google Cloud Platform and have an active project (learn how to set up GCP).
- Hold either the
BigQuery AdminorBigQuery Data Ownerrole.
Importing Costs from Multiple Ads Accounts
Important #1If you need to import costs from multiple Ads accounts, you must create a separate pipeline for each account.
Important #2Each user in an OWOX BI project can create up to 100 Google Ads → Google BigQuery pipelines. This limit is due to the restriction of 100 refresh tokens per Google Account per OAuth 2.0 client ID.
Step-by-step Setup
Step 1: On the Workspace page, click the ‘New’ button and select the 'Pipeline' option from the drop-down menu.
Step 2: As a source, select 'Google Ads.'
Step 3: Choose the pipeline 'Google Ads → Google BigQuery' and click the 'Create & Setup' button.
Step 4: The new pipeline is successfully created in ‘Draft’ status. To start data import, configure pipeline settings, including access to the source, and destination dataset.
Step 5: Set up source data:
5.1. Click on the ‘Source access’ section.
5.2. In the opened dialog, click “Continue with Google” to provide access for the OWOX BI app to your Ads account
5.3. In the Google sign-in window, choose the account you use with Google Ads.
5.4. Provide access to the OWOX BI app and click the 'Allow' button.
5.5. After successfully granting access, you will see a list of Ads accounts organized under MCC accounts. Select the Ads account from which you wish to import costs.
5.6. Click the ‘Save’ button to apply changes and close the dialog.
A green marker in the ‘Source access’ section confirms successful setup.
Step 6: Set up destination dataset:
6.1. Click on the ‘Destination dataset’ section.
6.2. In the opened dialog, choose a shared dataset from the list or click ‘Grant access…’ to add a new dataset following the instructions.
Optionally, after providing access to the GCP project, create a new dataset in the selected location.
Click the ‘Grant Access’ button to create a new dataset and provide access to it.
6.3. Select your dataset in the list of shared datasets, then click the ‘Save’ button to close the ‘List of shared’ dialog.
6.4. If everything is executed correctly, the dialog will automatically close. Therefore, a green marker with the name project.dataset.table will appear in the "Destination dataset" section.
(Optional) Step 7: Choose the tables and fields you wish to import. Click on the section:
In the dialog that appears, you'll find a complete list of tables available for import. All Google Ads costs are included in 5 tables, already selected by default. With the OWOX BI Pipeline, you have the option to import additional Google Ads data. Learn more
Optionally, select the tables you need from the list and then click the ‘Save’ button.
(Optional) Step 8: To adjust the Refresh window, click on the section:
In the dialog that appears, select a period of up to 30 days back for updating your costs. Learn more
To confirm your changes, click the 'Save' button.
Step 9: Activate the pipeline by clicking the ‘Activate’ button.
The pipeline status will change from ‘Draft’ to ‘Active.’
You're done. Tomorrow, the pipeline will start its first run.
Scheduling the Data Imports
Each day, your data will be available in the Google Ads cabinet at 3:00 AM in the timezone of the cabinet. Therefore, in the pipeline settings, we recommend scheduling the pipeline run between 3:00 and 4:00 AM in the same time zone.
Read more about when OWOX BI starts importing data from ad service to Google BigQuery
How to import historical data
The pipeline has been successfully created. Click the ‘Get data for the past period’ button to retrieve historical data. Select the start date and click the ‘Run once’ button.
The pipeline will start a manual run to import historical data.
NoteWhile the pipeline is in execution (status: Running), you cannot manually initiate another run. You must wait for the current run to complete before starting a new one.
After finishing the run, open your Google BigQuery dataset to check the resulting data.
View all pipeline runs on the ‘Run history’ tab.
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