When dealing with data, many provider names come up for tool recommendations, and on top of that list is Google. It offers modern tools for almost every aspect of data management. Two of the well-known tools provided by Google are Google Ads and BigQuery. 

Google Ads is a leading advertising platform that allows you to create and run advertisements for your target audience. The platform provides several features, such as a keyword planner, performance analytics, and campaign manager for efficient marketing and advertising. 

On the other hand, BigQuery is a serverless data warehouse that enables you to store and manage huge datasets in real time. It is part of the Google Cloud Platform (GCP) and is specially designed for complex analytics.

You can leverage the advertising capabilities of Google Ads and the data management capabilities of BigQuery by connecting both tools. This article will discuss Google ads data integration to Google BigQuery using two straightforward methods. 

Why Replicate Data From Google Ads to BigQuery?

Replicating data from Google Ads to BigQuery can significantly enhance your ability as a marketer to take meaningful insights from data and make more data-driven decisions. Here are some specific reasons for considering the migration of data from Google Ad Manager to BigQuery: 

• Centralized Data: In most cases, advertising data travels to multiple data sources and platforms for data analysis and other tasks. Moving Google Ads data to BigQuery centralizes the advertising data in one location, streamlining the data management process. 
• ‍Detailed Insights From Campaigns: Robust querying features of BigQuery allow you to do a granular analysis of Google Ads campaigns. This can include analyzing performance data at various levels, such as ad group, keyword, and ad levels. Additionally, you can define custom metrics according to your specific analytical needs to achieve meaningful data.  
• ‍Handle Large Datasets: If you run extensive advertising campaigns, you must deal with large amounts of data in real time. The distributed processing architecture of BigQuery allows you to manage huge loads of datasets efficiently and ensures that performance doesn't compromise as the data volume grows. 
• ‍Integration with Other Sources: BigQuery enables you to integrate seamlessly with many data sources besides Google Ads. This capability provides a holistic view of your business data by combining information from other sources such as CRM systems, Google Analytics, or other analytical platforms.

Methods to Integrate Google Ads to BigQuery

• Method 1: Using Airbyte to connect Google Ads to BigQuery. 
• ‍Method 2: Using BigQuery Data Transfer Service to integrate Google Ads into BigQuery. 

Method 1: Using Airbyte to Connect Google Ads to BigQuery

In this method, you’ll learn to use Airbyte to synchronize data from Google Ads to BigQuery. Airbyte is a cloud-based data integration tool that provides automated, reliable, and scalable solutions for your ETL workflows. Below is a step-by-step guide to this process: 

Step 1: Configure Google Ads As a Source

• Create or log in to your Airbyte account. 
• Once you are logged in, click on the Sources tab on the left navigation bar on the home page. 

• Use the search box on top to locate the Google Ads connector. Once you see the Google Ads connector, click on it. 

• You’ll be redirected to the Create a source page. Fill in the details like Source name and Customer IDs. 

• After filling in the details, sign in to your Google account from which you have activated Google Ads. 
• Click on Set up source. 

Step 2: Configure Google BigQuery As a Destination

• After setting up the source, click on the Destinations tab from the left just below Sources. 
• Look for the search box and type in BigQuery. Then, click on the BigQuery connector. 

• On the Create a destination page, fill in the connection details, including Destination name, Project ID, Dataset Location, and Default Dataset ID. 

• Select the Loading Method between: GCS Staging and Standard Inserts. The first method writes large batches of records to a file, uploads the file to GCS, then uses COPY INTO to load your data into BigQuery. It provides best-in-class speed, reliability, and scalability and is the recommended loading method. However the Standard Inserts method does direct loading using SQL INSERT statements. This method is suggested only for quick testing. 

• Provide the Service Account Key JSON (required for cloud, optional for open-source). Click on Set up destination. 

Step 3: Create a Connection Between Google Ads And BigQuery

• Once the source and destination are configured, you must establish a connection within Airbyte. You can click the Connections tab on the left navigation bar or select Create a new connection after setting up the destination. 

• Select Google Ads as a source (Step 1) and BigQuery as a destination (Step 2) to establish a connection. 
• Provide a unique Connection Name and configure connection details according to your requirements. You can select Replication frequency, tweak the Streams section, and select sync mode. 
• Lastly, click on Set up connection and run sync by clicking Sync now. 

That's all. You have completed connecting Google Ad Manager to BigQuery within a few clicks using Airbyte. 

Method 2: Using BigQuery Data Transfer Service to Integrate Google Ads Data Into BigQuery

In this method, you’ll know how to manually replicate data from Google Ads to BigQuery using BigQuery Data Transfer Service. This service, provided for Google Ads, lets you automate the management and scheduling of data loads for Google Ads reporting data. Start by activating the BigQuery Data Transfer Service, then create a BigQuery dataset for storing the data, and finally, transfer the data by configuring specific details. Here is a detailed guide: 

Prerequisites

• A Google Cloud account.
• Google Ads Customer ID. 

Required Permissions

Ensure you have the following required permissions for the transfer: 

• Read access to the Customer ID of Google Ads that is used to transfer the data.
• bigquery.transfers.update permissions for creating a transfer. 
• bigquery.datasets.get and bigquery.datasets.update both the permissions on the dataset you want to store the data. 

Step 1: Create a Project And Enable BigQuery API

• In the Google Cloud console, navigate to the project selector page.
• Select a project or create one. 
• Verify that the BigQuery API is already activated for the existing project. If not, you can enable it from the BigQuery API page.

Step 2: Activate BigQuery Data Transfer Service

• Go to the API library of Google Console and open the BigQuery Data Transfer API page. 
• Select the project from Step 1 in the dropdown menu.
• Click the ENABLE button. 

Step 3: Create a BigQuery Dataset to Store Google Ads Data

• Go to the BigQuery page. 
• In the Explorer panel, create a dataset for your project. 
• Click on Actions > Create dataset. 
• On the Create data set page, enter the unique dataset name for Data set ID, choose the geographic location for Location type, and configure other required details. 

• Click CREATE DATA SET.

Step 4: Create Google Ads Data Transfer Using Console

• Again, navigate to the BigQuery page in Google Console. 
• Click on the Data transfers section from the left navigation bar.

• On the Data transfers page, click on + CREATE TRANSFER.

• Select Google Ads as the Source option in the Source type section.

• Enter a unique transfer name for the Display name in the Transfer config name section. 

• Then, on Schedule options: 
• Select the frequency at which you want to conduct the transfer under Repeat Frequency. There are three options to choose from: Hours, Days, and On-demand. If you choose Days, provide a time that is valid in UTC. 
• If applicable, select Start now or Start at a set time. 
• For Dataset, choose the dataset you established in Step 3 in the Destination settings section.
• Then, in the Data source details section, enter Google Ads customer ID on the Customer ID text box and configure other details optimally. 

• Navigate to the Service menu and select a service account that is associated with the Google Cloud project. 
• You can choose to tweak the Notification options section as well. There are two options: Email Notifications and Pub/Sub notifications. Toggle the email notifications option to receive progress notifications by email. Click here to learn about Pub/Sub notification details. 

• Click Save. 

That concludes it. Follow the steps mentioned above carefully, and you can quickly integrate the data from Google Ad Manager to BigQuery. 

Conclusion

You have learned two straightforward approaches to integrating Google Ads to BigQuery. Both methods have their use cases and benefits. The first method uses Airbyte to automate the connection between both tools. You have to set up the source and destination, and just like that, you’re done with the task within a few clicks. 

In contrast, the other method uses BigQuery Data Transfer Service to integrate data, requiring more effort than the first one. You have to manually mention all the complex configurations required for the transfer in Google Cloud.

We suggest using Airbyte to automate the whole process of Ads data integration to Google Bigquery. In addition, you can take advantage of its user-friendly interface, modern orchestration capabilities, and more than 300 pre-built connectors, which give you many options for connecting sources and destinations.