Sending Google Analytics data to BigQuery without 360

If you want to send Google Analytics data to BigQuery without using Google Analytics 360 then follow the steps below:

Step-1: While logged into your Google account, navigate to your Google cloud platform account at https://console.cloud.google.com/

You should now see a screen like the one below (here I am assuming that you are using the Google cloud platform for the first time):

Step-2: Type bigquery in the search box:

Step-3: Click on the first search result:

You should now see a screen like the one below:

You now have access to the BigQuery Sandbox.

The sandbox let you use the Google cloud console for forever free without creating your billing account or enabling billing for your BigQuery project.

However, the BigQuery sandbox comes with certain limitations related to data storage and processing query data.

To overcome these limitations, you should upgrade your BigQuery Sandbox account by setting up your billing.

When you set up your billing, Google gives you $300 of free credit to explore any of the Google cloud products including BigQuery.

Don’t worry Google will not charge your credit card until you manually upgrade to the paid account.

Whether or not you enable billing, you can use Google Big Query for free as long as your account remains within the free usage limits.

Step-4: Click on the ‘Activate’ button at the top right hand side to start your free trial of Google cloud platform:

Step-5: Select your billing country from the ‘Country’ drop-down menu and then read and accept the terms of service by clicking on the checkbox:

Step-6: Click on the ‘Continue’ button.

Step-7: Enter your name, address and credit card details and then click on the ‘Start my free trial’ button:

Step-8: Navigate to: https://console.cloud.google.com/bigquery and then at the bottom of your screen click on the ‘Enable’ button next to ‘Try search and autocomplete powered by Data Catalog‘:

Step-9: Click on the ‘OPT-IN’ button:

Step-10: Click on the ‘Push App Test’ drop-down menu:

Step-11: Click on the ‘New Project’ button:

Step-12: Name your project say ‘Google Analytics’ and then click on the ‘Create’ button:

We are going to use this new project for collecting data from Google Analytics.

Step-13: Click on the ‘Push App Test’ drop-down menu:

Step-14: Click on the name of your new project (in our case ‘Google Analytics’):

You are now in the Google Analytics project.

At this point, you can either use the Google Analytics sample dataset for BigQuery or pull your own Google Analytics data.

Lets first access the Google Analytics sample dataset for BigQuery.

Step-15: Type ‘public’ in the search box which is below ‘Resources‘:

Step-16: Click on the project ‘bigquery-public-data‘:

Step-17: Type ‘ga_sessions‘ in the search box which is below ‘Resources‘:

Step-18: Click on the ‘ga_sessions_(366)’ data table:

The ‘ga_sessions_’ is the name of the data table under the google_analytics_sample dataset. This table contains the Google Analytics sample dataset for BigQuery

You now have access to the Google Analytics sample dataset. At this point you can run SQL queries to retrieve a particular set of data:

Now instead of using the Google Analytics sample data set, let use the data from our own Google Analytics account.

Step-19: Click on the cross button in the search box which is below ‘Resources’:

Step-20: Click on the project ID (this ID could be different in your case):

Step-21: On the right-hand side of your screen, find and click on the button ‘Create Dataset’:

Step-22: Name your data set (say GA_data_set) and then click on the ‘create data set’ button at the bottom:

We are going to use this new data set for storing data from Google Analytics.

You would now need to use a third-party solution for sending Google Analytics Data to Big Query. This is going to cost you based on your account usage.

Regardless of how much it cost you, it would most likely still be cheaper than paying $150k per year to Google for using the GA360 (which comes with the connection to BigQuery).

You can either search for such third party solutions online or use the one that I use which is DataDDo. They provide a free 14 days trial of their solution. No credit card required.

Step-23: Navigate to https://www.dataddo.com/, click on the button ‘Try DataDo Free’ and then set up your account by following the on-screen instructions:

Step-24: Once you have created your account then navigate to the page: https://app.dataddo.com/

Step-25: Close the video pop-up box by clicking on the close button:

You should now see an screen like the one below:

Step-26: Scroll-down the screen and then click on the ‘Google Analytics’ data source:

Step-27: Click on the ‘Authorize’ button to authorize dataddo to access your Google Analytics account:

Step-28: Click on the Google account which is associated with your Google Analytics account:

Step-29: Click on the ‘Allow’ button:

Step-30: Select your Google Analytics account, property and view which you want to use for pulling your data into BigQuery:

Step-31: Click on the ‘Next >’ button:

Step-32: Name your data source and then select the metrics and dimensions you want to pull in your BigQuery project:

Step-33: Click on the ‘Next >’ button.

Step-34: Again Click on the ‘Next >’ button:

Step-35: Click on ‘Data Warehouse’:

Step-36: Keep the recommended setup for your data warehouse and then click on the ‘See Preview’ button:

Step-37: Click on the ‘Save and create flow’ button:

Step-38: Click on the ‘Add Destination’ to add the destination data source:

Step-39: Scroll down your screen and then click on ‘Create new destination’ button:

Step-40: Click on the ‘Google Big Query’:

Step-41: Click on the ‘Authorize’ button to authorize dataddo to access your Google cloud account:

Step-42: Click on the Google account which is associated with your Google Cloud account:

Step-43: Click on the ‘Allow’ button:

Step-44: Click on the ‘Next’ button:

Step-45: Enter your destination name (say ‘Google Big Query’), select your BigQuery project and the data set:

Here we selected the project and the data set which we created earlier.

Step-46: Click on the ‘Connection Check’ button:

You should now see a screen like the one below:

Step-47: Click on the ‘Create Flow’ button at the top right hand side:

Step-48: Name your data flow (say ‘Google Analytics to BigQuery’):

Step-49: Enter the name of the database table which you want to use for collecting Google Analytics data in Big Query. You can give any name you want:

Step-50: Select the time schedule, timezone and data sync period. These settings determine when the dataddo should pull data from your Google Analytics data into BigQuery:

Step-51: Click on the ‘Create Flow’ button at the top right hand side.

You should now see an overlay like the one below. Do not close this overlay:

Step-52: Navigate back to your Google cloud BigQuery account (https://console.cloud.google.com/bigquery) and make sure that ‘Google Analytics’ project is selected.

Step-53: Click on your project ID (in my case the id is unified-academy-301114):

Step-54: Click on the ‘GA_data_set‘:

Step-55: Click on the ‘CREATE TABLE’ button:

Step-56: Navigate back to your Dataddo account and follow the instructions for setting up your Google Big Query table:

Step-57: According to my instructions, I need to do the following:

1) Set the table name to ‘google_analytics

2) Select “Edit as text” and then copy and paste the table definition below:
gadate:DATETIME,
gasourcemedium:STRING,
gasessions:NUMERIC,
gapageviews:NUMERIC,
gausers:NUMERIC,
gaavgtimeonpage:NUMERIC,
gagoalcompletionsall:NUMERIC,
gatransactions:NUMERIC

Step-58: Click on the ‘Create Table’ button.

Step-59: Navigate back to your Dataddo account and click on the close button:

You should now see a screen like the one below:

Step-60: Click on the ‘Force run’ button at the very bottom of your screen:

Step-61: Type CONFIRM in capital letters in the text box and then click on the ‘Insert data to storage’ button:

Step-62: Navigate back to your Google cloud account and then click on the ‘google_analytics’ data table under the data set ‘GA_data_set’:

Step-63: Click on the ‘Preview’ tab. You should now be able to see your Google Analytics data in your Big Query data table:

At this point, you can query a particular set of data by using SQL:

That’s how you can send Google Analytics data to Big Query without using Google Analytics 360.

Sending Google Analytics 4 data to Big Query

Google Analytics 4 provides a free connection to the Big Query. So you don’t need to use a third-party solution for that.

This make sending GA4 data to Big Query bit different.

To send Google Analytics 4 data to Google Big Query, check out this article: How to connect GA4 (Google Analytics 4) with BigQuery

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