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Latest Updates on Google Data Analytics (June 2022)

The highlights of the updates on BigQuery, Data Studio, Google Analytics (GA) & Google Tag Manager (GTM). By Alexander Junke

In this blog post, I want to summarize the new releases from the Google tools, that we use daily in datadice. Therefore I want to give an overview of the new features of BigQuery, Data Studio, Google Analytics and Google Tag Manager. Furthermore, I will focus on the releases that I consider to be the most important ones and I will also name some other changes that were made.

If you want to take a closer look, here you can find the Release Notes from BigQuery, Data Studio, Google Analytics & Google Tag Manager.


Set Default Configurations

You can set some configurations on an organization or project level. Currently, there are three settings supported:

  • default_time_zone: You can choose a default time zone, which is taken when a time zone-dependent SQL function has no time zone value specified
  • Default_kms_key_name: Is the default Cloud Key Management Service key for encrypting the data
  • default_query_job _timeout_ms: Time after a query job gets stopped in milliseconds (between 10 minutes and 6 hours)

To do these settings you have to do the following:


 `region-eu.default_time_zone `= Europe/Berlin,

 `region-eu.default_kms_key_name` = KEY,

 `region-eu.default_query_job_timeout_ms` = 1900000);

The time zone and time-out parameters are interesting for us. We have projects where we use different time zones and with the time-out parameter, you can control your query run times.

Query queues

This new feature comes into action when you have a lot of queries at the same time. You can set a limit, on how many queries should run at the same time or BigQuery calculate a fitting limit for you.

If this limit is reached, all additional queries go into a queue and get executed step by step, when free capacity is available.

Further information you can find here.

SQL translation services

The SQL translation service has been available for some months already. Google is still improving it and it is generally available now. Teradata SQL and Amazon Redshift SQL can already be translated and some translations are in preview, e.g. Oracle SQL, Snowflake SQL, and Apache Spark SQL.

All these dialects are supported if you want to translate SQL query files (Batch) or directly in the SQL workspace (Interactive).

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Select the needed SQL dialect

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An interactive SQL translation

Explore data with Data Studio

Google added a new feature to show again the good connection between BigQuery and Data Studio.

When you look at the resulting table of a query, you can use and visualize this data in a Data Studio report.

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After clicking on “Explore with Data Studio”, a new Data Studio report opens and shows a table and a chart with some dimensions and metrics already set.

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Automatically created report

Then you can also change the report and adjust it to your needs, to get some more insights into the data.

Data Studio

Linking API

This is a huge thing and we are still checking out, what this new kind of API is capable of. Due to that, I am pretty sure that I will write an own blog post about it in the next few days, but let us take a first look into it. Especially I want to show what are the ideas behind this new feature.

The Linking API (before it was called Integration API) is out of beta now and got a lot of new features.

The general idea is to enrich the access link to a Data Studio report you send to another person, to customize the experience the person gets. Furthermore, you can also configure the Data Studio reports just with the URL you are using.

The URL has the following structure:

So the path is always the same and all the configurations are made in the parameters. E.g. the parameter c.reportId needs the Id of the report. Additionally, with c.pageId you can also define the starting page.

You can also copy or create new dashboards with these URLs. We will take a look into this in the upcoming Linking API blog post.

Further Information you can find here.

New data panel

This is a nice new feature, which makes your daily workflow easier. Google added a new module on the right side in the edit mode.

There you see all data sources which are connected with the report and you can also add new data easily (Button: Add Data). You can expand a data source to see all available fields of this data source and you can create calculated fields.

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The new data panel

You also see easily which type of connector is used (in the screenshot above there are GSheets, BQ, and blended data sources in use). Per drag-and-drop you can add fields from the data source to the selected chart.

Service Accounts for data access

There is the possibility now, to use the credentials of a service account to access the data of a data source. This approach has some benefits, I would say the most important is that you do not lose access to the data if a person leaves the organization.

How can you do this?

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  • Then you have to create a Service Account in the same project, where the data is located
  • The Service Account needs the BigQuery Job User IAM role
  • Then in the Service Account Users Role field, you add the users who should have access to the Service Account and later to the connected data
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  • At the same place, you also have to grant access to the DS Service Agent and give it a role that has the permission iam.serviceAccount.getAccessToken (e.g. Service Account Token Creator)
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  • You can grant the Service Account access to the data on a project, dataset, and table level

Then the setup is done to use this Service Account for data access. A more detailed guide you can find here.

Google Analytics

Store data in the EU

An important change for companies and users in the European Union!

For Google Analytics there are additional domains available where the tracking data is stored on servers that are located in the EU.

I think you know the big discussions about this topic, due to the problems with the GDPR in the EU. Google started to tackle these problems.

To ensure this, you maybe have to update your content security policy configuration. How to do it, check out the GA Release Notes.

Behavioral modeling for consent mode

This feature wants to fill the gap of data you have in your GA properties, due to e.g. declined Cookie consent. To fill this gap, Google tries to estimate the missing user behavior data based on the available data.

Important: To use this feature you have to implement the Google Consent Mode features on your website.

To activate this modeling you have to go to Admin > Reporting Identity. For all the properties I have access to, this feature is not available. When you activated it, in the GA report you can check if it includes estimated data.

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Check if behavioral modeling is activated

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Report uses estimated data (picture taken from here)

Further information you find here.

Google Tag Manager

No further release for the Google Tag Manager.

Upcoming datadice blog posts for this month

  • Data Modeling in Y42 (Part 3) - Coming Soon
  • GA4 Engagement Metrics - Coming Soon