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  4. [Online] Getting Started with the GA4 BigQuery Export connector
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  4. [Online] Getting Started with the GA4 BigQuery Export connector

Getting Started with the GA4 BigQuery Export connector in Analytics Canvas

This article goes through the steps of connecting to your BigQuery export and importing data onto the Canvas. 

To connect to your GA4 BigQuery dataset, first permit the Analytics Canvas Service Account for your subscription to access the BigQuery project with your GA4 data in it.  

>> Learn more in this article from our knowledge base.

Once you have permitted access (following the steps in the article linked above), ensure that you create your Canvas in the same data location as your GA4 BigQuery dataset. Find the location of your BigQuery dataset within the Google BigQuery console by clicking on the dataset and reviewing the Dataset info tab.

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Create a canvas in the same region as the Data location of your Project and Dataset in BigQuery.

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To add a data location to your subscription, go to Admin > BigQuery Quota and Location

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On your canvas, you can now select from two methods of querying the GA4 tables in your BigQuery project.

  • GA4 BigQuery SQL Connector (visual UI to generate the SQL query)
  • BigQuery SQL Connector (for writing your own custom queries)

The Google Analytics connector generates the SQL based on user selections of dimensions and metrics.  The BigQuery SQL connector allows you to write your own SQL, or customize SQL produced by the Google Analytics connector. 

To connect to the GA4 BigQuery Export and use the SQL Builder, follow the steps outlined below.  To write your own SQL, go to the next section

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Accessing GA4 BigQuery SQL Connector with Analytics Canvas Online

  1. Select "New GA4 BigQuery Table" after dragging and dropping the Google Analytics data source onto the main canvas.  
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All users have access to the Google Demo Property.  You can use this property to explore the connector, making as many queries as you'd like.  

  1. Once you're ready to view your own data, click "+ Grant Access to GA4 BQ"

** In order to connect to your data in BigQuery, you must first permit the Service Account for your subscription to access the BigQuery project with your GA4 data in it.  Learn more in this article from our knowledge base. **

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  1. If you haven't already authorized a Google account with access to your GA4 property, click "Add a new Google Analytics 4 credential."  The list should contain at least one account that has at least "Viewer" access to the GA4 Property in Google Analytics that is linked to BigQuery. 
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  1. Next, the Service Account for your Analytics Canvas subscription will need permission to read your GA4 Property's data in BigQuery.  Follow these instructions on our knowledge-base if you haven't already completed this step.  If you've already permitted the Service Account, click "Scan".  It may take up to 10 minutes before permissions propagate.  Continue to rescan periodically until the property is shown. 

**  The scanning step might take a few minutes if you have a number of Properties, event params and user property values in your account. **

  1. Select your GA4 Project in BigQuery and click "Next Step: Edit Query". 

  2. In the query editor, you can select from the available dimensions and metrics and the SQL will be generated for you.  

    • You can click Run Query, then select the Preview tab to see a preview of the results.  Canvas will preview over the past 5 days. 
    • You can validate the query by clicking "Validate without running" to see if your query is valid and how many bytes it will process to return the result. 
  3. When you've completed your query, click "Next Step:Date Range"

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  1. Under Table Name, give your table a name.  You can find the table under this name in the Tables menu, and in the list of available tables in your Table library for GA4, shown each time you add a new GA4 input to the Canvas.  

  2. Select the date range for your query.  By default, Canvas will perform a historic load, then update the table on an incremental basis based on the number of days you enter for the refresh period.   

  3. When you've completed your query, click "Next Step:Submit".  If you included a date dimension, a date-partitioned table will now be added to your Canvas.  

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With the data on your Canvas, you can now preview it, profile it, prepare it for reporting, and publish to your preferred data destination! 

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Writing your own SQL using the BigQuery SQL Connector

Using the BigQuery SQL Connector in Analytics Canvas, you can write your own queries. Start by dragging the BigQuery SQL connector onto the main canvas. 

Adding an SQL Import block to the Canvas

Having already setup the account as discussed above and in this article, you can now write your SQL in the query window and land your data onto the Canvas.  To use the Date Parameters in your query, follow the directions in this article

If you run into any issues at all, please contact support@analyticscanvas.com.

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