ETL Facebook Ads data to Google BigQuery — 3 simple methods

ETL Facebook Ads data to Google BigQuery

Since its launch, Facebook’s advertising platform has severely competed with Google Ads. Since then, ad creators interested in investing their PPC have had to make a difficult choice between these two giants of the Internet industry. They often use both Facebook and Google to gather information. Advertising companies actively use the data obtained for:

  • control of the effectiveness of the advertising strategy;
  • observations of current trends;
  • creation of comprehensive strategies;
  • implementation of innovative ideas.

Despite its affiliation with Google, BigQuery remains an effective standalone solution that PPC marketers actively use for Facebook Ads to Google BigQuery.

There are currently three known methods of transferring information from Facebook Ads to Google BigQuery:

  • manual upload;
  • using a connector or data pipeline;
  • using the Renta store of advertising information.

More complex, complicated methods of automatic transfer of Facebook Ads to Google BigQuery content require significant material costs and non-standard technological solutions.

The manual upload of Facebook Ads information

Google BigQuery’s standard feature set includes importing information manually using a CSV file. Users accessing the Facebook Ads report can copy it to their information repository. The price of Facebook Ads to BigQuery is very reasonable.

To perform such actions, it is necessary to:

  1. Establish a new project in Google Cloud. It is possible to use the free test version of the product.
  2. Go to Google BigQuery. The previously created project will be available on this resource. In the Settings section, the user can replace the standard project name with their own.
  3. Select the information in the Facebook marketing API Manager that the user wants to transfer to Google BigQuery. To do this, it is necessary to upload by clicking on "Reports" and then activate data export.
  4. The information in the form of a .csv file will become available for saving to the hard disk of the user’s computer.
  5. Then you will need to go into Google BigQuery, select your project, and click on its identifier in the left half of the search bar.
  6. Activate the option to create a set of information.
  7. Think of a name for the new information block. Preferably, it should match the content that you plan to put in Google BigQuery.
  8. Check if the encryption method is activated and only create a set of information by running the same name option.

The resulting data will best be read in tabular form. To translate them into a table, you need to create one. To do this, select your project and activate the corresponding option in the left half of the navigation bar.

Afterward, you need to go to the “Source” tab and download the table. It will be easy to do. You will need the following:

  • select your previously saved Facebook report;
  • In the "Assignment" tab, use the search to find the name of an already created project and the name of a data set;
  • enter the table name – it must correspond to the content to be loaded.

Google BigQuery has a unique interface for loading and editing tables. You can use it to learn the information required for structuring Facebook Ads information tables.

To make it easy to process and analyze your analytics data, you can modify your table using the section and subsection settings option specifically provided for this purpose. It will allow you to separate the information by the time of receipt. As a result, the table will be divided into separate fragments, which will speed up the search and make data processing faster and more convenient.

The advanced options section will also help you process the information correctly. Here the user can set field delimiters, define skipped header lines, and perform other valuable actions with the edited data. You will need to put a comma as the field delimiter.

The Google BigQuery tabular data formation template includes additional parameters for setting delimiters. To finally form and structure the obtained information, you need to:

  1. Select the option to create a table, and then the information from Facebook Ads will be uploaded into the resulting data cluster. To check the upload status, you will need to check the history regularly.
  2. Switch to Google BigQuery and select your information set identifier.
  3. After performing the previous step, the user can create SQL queries to their BigQuery or Facebook stores and transfer the available information to Google Data Studio and other applications for further processing.

It would be best if you were sure to repeat the above procedure for any additional Facebook information clusters you wish to migrate. Regular repetition will also be helpful if you want the information to be constantly updated. Google’s service offers users a complete guide to manual data transfer in Google BigQuery. It also details the use of JSON and provides help sections.

Application of connectors and conveyors

You can translate advertising content in Google BigQuery not only manually. An alternative way is to use data conveyors or connectors. Powerful applications have been created for this purpose, among which the most famous are:

  • Supermetrics;
  • Improvado;
  • Funnel.

To transfer data from Facebook to Google BigQuery, perform the following steps:

  1. Subscribe to the free release of Supermetrics for BigQuery. Be prepared for the fact that you will get access to this program not immediately.
  2. Place data source of Facebook Ads in Supermetrics.
  3. Form a new Google Cloud project in the trial version.
  4. Next, you will be taken to the main checklist — select item 3 to get to the Google Cloud Platform Marketplace.
  5. Click the "Facebook Ads by Supermetrics" tab and select sign-up.
  6. Find the project you created earlier. Its name will be the same. You can change it by going to the settings section.
  7. Switch to BigQuery and select the name of the project you created in the left panel.
  8. Activate data set creation, enter location information and then save the entered data.

The system will indicate to the user where to create a new information list. To do this, select Transfers on the left side of the screen and then click on the "Create translation" tab.

Google Big Query provides the ability to create a new transfer of information from Facebook Ads. In addition, you can set the necessary configurations for the transfer in a unique environment.

To perform the above tasks to translate Facebook ads to Google BigQuery information, the user will need the following:

  • to source Facebook Ads by Supermetrics;
  • to assign a name to the transmission configuration – it must match the name of the task to implement;
  • to adjust the timing.

The regulation’s mandatory parameters include when the accumulated information is updated. The user can also manually set the start of the update. It is required to specify a start date and a deadline for this procedure. The user must assign a header for the information available in BigQuery; it will be considered the identifier of this data segment. To do this, on the information set creation tab, you will need to specify the name of the identifier, the path to the information, the deadline time of the tabular data, and the encryption method.

Google BigQuery includes certain functionality that allows you to configure essential translation options. To activate the connector, go to the "External Connections" tab and click on the "Connect Source" button. Next, you will need to have Supermetrics registered as an external connector.

It is possible to access Supermetrics for BigQuery using the popup of the same name. In addition, it may be necessary to log in to Facebook Ads. This window is specifically designed for the user to launch the connector. He will also need to select his advertising accounts to transfer information.

After performing all the above steps, the archive will begin to fill with new information, and the user can get back to BigQuery to return to their resources. To download historical data, the user should follow the official Supermetrics documentation.

Using the Renta advertising interface to transfer information from Facebook to BigQuery

The Renta Customer Data Integration software is a simple tool for advertising professionals to organize and replenish the BigQuery information archive using data from Facebook Ads. Renta’s tasks include controlling the Google cloud platform and activating information clusters. To take advantage of Renta’s valuable features, it is necessary to:

  1. Complete registration in the service.
  2. Load Facebook Ads data sources. This procedure is performed when the user creates an account.
  3. Select ADI in the main field and click to activate the repository in the window that appears. The Renta Advertising Data Infrastructure tools will help users launch the data warehouse to create a unique PPC information archive.

After the actions mentioned above, Renta will automatically load BigQuery data and enable five freely distributable versions of the data for the company. When all this is created and the monthly data update is activated, the user will have access to an archive of information with a list of all current versions.

The Renta software environment allows its registered visitors to run up to 40 different views (versions) of advertising information. To activate a view in BigQuery, it is necessary to click on its name or select the "Open in BigQuery" option. The user can then work with the entire BigQuery archive.

Opening access to the information in BigQuery by clicking on the name of the view is also among the valuable features of the Renta ad information service. When the information transfer is complete, the archive will be fully replenished. Users can make queries in BigQuery or transfer them to Google Data Studio and other third-party services. This will be easy to do. So, if you need to use the advanced view, turn on the corresponding checkbox and click on the pencil at the top of the table. Then, you will need to select the "Enabled" state in the View Status Management window.

The Renta has a form where users can activate or deactivate the information views. To do this, use the pencil image to control the view. In addition, it is possible to set how and how often the information should be updated and the optimal amount of data to be updated by the view. After editing all the configuration settings, the user must save them by running the same name option. At the Renta Support Center, you can find complete information about all of ADI Renta’s features, including archive management and free ADI Data Studio kits.

PPC’s voluminous information repository helps all professionals whose job is to implement an effective AD campaign. On the contrary, Renta archives are designed at the company level to simplify access to important information. In addition, open access to the API is implemented.

If you need additional insights or are interested in the possibilities that an up-to-date archive of advertising data can provide, consult the experts at Renta. They will help you to learn more intelligently using valuable information from social media and advertising platforms.

Karuna Singh

Greetings to everyone. I am Karuna Singh, I am a writer and blogger since 2018. I have written 250+ articles and generated targeted traffic. Through this blog blogEarns, I want to help many fellow bloggers at every stage of their blogging journey and create a passive income stream from their blog.

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