Latest Updates on Google Data Analytics (February 2022)
The highlights of the updates on BigQuery, Looker Studio (formerly called Google 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, Looker Studio (formerly called Google 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, Looker Studio (formerly called Google Data Studio), Google Analytics & Google Tag Manager.
BigQuery
WITH Recursive
Recursive algorithms are a standard approach in programming languages. So to repeat a task with some kind of incremental/decremental change in every step is also possible inside BigQuery now.
Let us quickly go through an example:
WITH RECURSIVE generate_dates AS
(( SELECT CAST(‘2021–01–01’AS DATE) AS date) UNION ALL (SELECT DATE_ADD(date, INTERVAL 1 DAY) AS date FROM generate_dates WHERE date < ‘2021–01–31’))
SELECT date FROM generate_dates ORDER BY 1
When you are creating a WITH statement you can decide if it should be recursive or not. So in the first parenthesis, you are choosing the starting point of the algorithm. The second statement defines the incremental change of the data in every step and the condition when the recursion is finished.
With the example, we are creating a column for every day in January 2021. The date 31.01.2021 is also part of the result because at first it calculates and writes the result in the table and then it checks the condition.
Note: There are even simpler approaches to generate this kind of data, e.g.using GENERATE_DATE_ARRAY().
Table clones
BigQuery offers already a lot of possibilities to copy a table. For a few months, you can also create a snapshot to save or get back a defined version of a table.
Now it is also possible to create a clone out of a table. So then you also have a base table and a cloned table. The big difference to the other approaches is, If you change nothing inside the copied table there are no storage costs for this table. There are just storage costs for all differences between the base and cloned table.
The statement to create a cloned table is the following:
CREATE TABLE
project_name.datase_name.table_clone
CLONE project_name.datase_name.table
Remote functions
BigQuery has already User-defined functions (UDFs), where you can create more complex algorithms, with SQL or Javascript, and use them inside your ETLs.
With Remote functions, you can build functionalities in other languages than SQL or JS and use more different libraries. For that, you have to build an endpoint in Google Cloud Functions, create a remote function in BigQuery and use it in your Queries. You can take a look here to get some more insights.
Looker Studio
BigQuery Connector data freshness
A big obstacle of the strong connection between Looker Studio and BigQuery is eliminated. Before the change, the data freshness was minimum 15 minutes. That means the data in the report is getting updated every 15 minutes (except if you refresh the data on your own).
Now it is even possible to put the schedule time to every minute. With that, it is possible to create (near)-realtime reporting. But for sure your costs are increasing when you are updating the data again and again. To change the data freshness of the datasource, you have to do the following:
Improved Data Blending
Looker Studio improved in a lot of ways the data blending in your reports. We will write an extra blog post in the next days about this topic because there are a lot of new features to cover. Here you see the new blending menu:
I just want to list the most important changes in this blog post. More detailed information comes in the next blog post.
- The new look of the blending menu
- 5 different kinds of join operations (before it was always LEFT JOIN)
- Different join conditions in each join
Google Maps Heatmaps
Looker Studio added a new Google Maps type as a possible chart type. The Google Maps Heatmap is new nice looking visualization. Depending on the selected metric the color of the circles are changing. You can change the color for the three different intensities (default: green, yellow, red), the size of the circles and many more.
Page Navigation in embedded reports
When you are not offering custom navigation inside your report it was not really intuitive to navigate through embedded reports. Now you can use one of the 3 standard navigation types (Left, Top Left or Tabs). And you also have to activate it in the embedded report:
Google Analytics
BigQuery Export Filtering in GA4
When you want to export your GA4 data to BigQuery, you can choose the events which should be excluded in the export. This is especially interesting when you exceed the 1 million events per day limit.
You can type in the Event Names you want to exclude (important when you have this event in the future, but should not be part of the export) or you get a list of all available events.
GA4 with Display & Video 360 data
You are now able to link your Display & Video 360 data with your Google Analytics 4 property to see the data also in the GA4 reports. You can connect it in the Admin section of your GA4 Property.
Google Tag Manager
No further release for the Google Tag Manager.
Upcoming datadice blog posts for this month
- New Looker Studio blending menu — here
- The end of Google’s Universal Analytics has a date — here
- Friendly Intro to Y42 — here
Further Links
This post is part of the new features in the Google cloud series from datadice and gives you detailed insights about a new feature in BigQuery or Looker Studio.
We also started with our own YouTube channel. We talk about important DWH, BigQuery, Looker Studio and many more topics. Check out the channel here.
If you want to learn more about how to use Google Looker Studio and take it to the next level in combination with BigQuery, check our Udemy course here.
If you are looking for help to set up a modern and cost-efficient data warehouse or analytical dashboards, send us an email to hello@datadice.io and we will schedule a call.
