6-MINUTE READ · By Riku Mikkonen

With the amount of marketing data produced daily, demands presented for storage and computing power are on the rise. Many marketers are faced with insufficient capabilities and spend a lot of time waiting for reports. Could a marketing data warehouse using Google BigQuery be the solution they are looking for?

How can you set up your marketing data warehouse in BigQuery? In this article we will:

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1. Set up a BigQuery project

To get started, you only need a Google Cloud account and platforms to pull from. To begin transferring data to BigQuery, we need to set up a BigQuery project that will contain all of our data. Opening the Google BigQuery page on the Google Cloud console presents you with the button to create a new project.

Setup your new BigQuery project by clicking "New Project"

Clicking on the “New Project” button, you are presented with a screen to input the name and other information about your project. Insert the information and click “Create”.

Input a project name, select a billing acount, organization and a data location.

2. Configuring the connector

After setting up a BigQuery project, we are ready to configure data transfers to our new data warehouse.

To begin, open the side menu and click the “Marketplace” button.

GCP-marketplace

In the marketplace, search for Supermetrics. This presents you a the list of different data sources you can connect. Select the data source you want to connect to BigQuery. For the purposes of this example, we are selecting Facebook Ads as our connector of choice.

Click on enroll to add a data source

After selecting your connector from the list, click “Enroll” to add the data source to your project.

Select an appropriate project to add your data connection

Select the BigQuery project created earlier and click “Continue”.

3. Create a data transfer

Clicking on "create dataset" helps you create a dataset

After enrolling and adding the data connector to your BigQuery project, open up the Google Cloud menu and navigate to the BigQuery console. When in the BigQuery console, click on the “Create Dataset” button.

Input Dataset ID, select a data location and table expiration.

Give the dataset a name and select a data center location. Selecting your data location is optional, but for better performance,it is a good practice to pick the closest data location to you.

This shows you the transfers tab

Click on create to create a data transfer

After creating a dataset, select “Transfers” from the side menu and click “+CREATE”.

Select a data source type from the drop-down menu

From the drop-down menu, select your data source from the options.

Give a name to the transfer, set a schedule

Give your data transfer a descriptive name and set the transfer schedule to fit your planned data refresh scheme.

Give a name to your dataset

Select the dataset where you want the data to be transferred to.

Click on connect source

Click “Connect source” to finalize the settings.

Accept data connection agreement

Before we can start our transfer, we need to authorize the connection on both the destination and the source side. After you have gone through the data connector agreement, click “Accept Agreement”.

Sign in with Google credentials to authorize the connector

After accepting the agreement, you are presented with a screen to sign in with your Google credentials. Click on the “Sign in with Google” -button and enter your credentials.

Authorize the Facebook connection

After signing with your Google credentials,  you will see a prompt to authorize the connection to Facebook Ads. Click on the authorization button and login with your Facebook credentials.

Configure the data source and conversion window

After authorizing the connection to Facebook, you are presented with a screen where you can select what data you wish to extract. Select the Facebook Ads account and campaigns you would like to extract. You can customize the transfers to contain the conversion window and timezones to your liking.

Congratulations, everything is set up! The data sources are connected and data is automatically transferred to your new marketing data warehouse. You are now ready to utilize the capabilities brought on by data warehousing.

Data Warehousing can be utilized as a source for Data Studio reports

Google BigQuery can be connected to a variety of different Business Intelligence and Dashboarding tools. Learn how to connect to Google Data Studio.

In summary

With these simple steps, a marketing data warehouse can be set up within minutes. We set up our first BigQuery project and configured regularly scheduled transfers from different sources creating an unified marketing repository for all of our marketing data. 

Want to give it a try? Try out Supermetrics for BigQuery with a free 14-day trial and experience first-hand how quickly you can set up your own marketing data warehouse.

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