Dec 11, 2022

5 min read

Latest Updates on Google Data Analytics (November 2022)

The highlights of the updates on BigQuery, Looker 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, 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, Google Analytics & Google Tag Manager.

BigQuery

Query execution graph

When you are running a query in BigQuery, then you can look into some execution details during and after the execution.

Google added the tab “Execution Graph” to show the flow of the execution in a more visual way.

In the Screenshot above you can see the start of the execution and in the right window, you see the total graph and the part you are looking at (the blue box). With the settings above, e.g. Highlight top stages by duration, BigQuery show which steps take longer or which are intense processing steps, with different colors.

A really nice feature and especially useful, if you need to design queries that need to be highly efficient.

Object Tables

BigQuery is still establishing new ways to interact with unstructured data (with the help of BigLake and Google Cloud Storage).

An Object Table is a read-only table in BigQuery and inside the table, you can find data that is located (unstructured) in Google Cloud Storage. The main purpose of this is to analyze unstructured data, e.g. for ML Models.

To create an Object Table you have to connect BigQuery with Cloud Storage at first.

Then you can code a query to create an external table in BigQuery.

CREATE EXTERNAL TABLE `data_lake_test.name_of_table`
WITH CONNECTION `eu.test-data-lake`
object_metadata = ‘SIMPLE’,
uris = [‘gs://name-of-the-bucket’]

This is currently not working for us, because we get the error message: “object_metadata is unsupported in this project” and it looks like it is a common error, Google has to fix (Ticket).

A nice video to understand the idea behind “Object Tables” in BigQuery you can find here.

And here you can find the introduction for Object Tables in the documentation (+ the default schema of the table).

Metadata caching

Another small new feature is, that you can enable metadata caching for the purpose of better performance for BigLake tables and object tables. When you are creating the tables you have to enable this caching and you also have to define, for how long the information should be saved.

The parameter is max_staleness. If it is 0 (default value), then the metadata caching is disabled. “Interval 1 DAY” is for example a valid value

CREATE EXTERNAL TABLE `data_lake_test.name_of_table`
WITH CONNECTION `eu.test-data-lake`
object_metadata = ‘SIMPLE’,
uris = [‘gs://name-of-the-bucket’],
max_staleness = INTERVAL 1 DAY

Looker Studio

Chart Editing Panel

In one of my last blog posts I complained about it and now it is finally there:

You can resize the chart editing panel!

A small but very nice feature. If you have a lot of long column names, now you can see (hopefully) the full name directly, without the annoying mouse hovering over the field.

Zoom control

Google added some options for the zoom control for your reports. You can now also select from one of the options “Fit all”, “Fit width”, or “Default” (default selection). With these options, you can easily expand the report view size to the full potential of your current screen.

Google Analytics

Custom fields as primary dimensions

Google is still improving the customizability of the reports so that the analysts can build their own visualizations.

It was already possible to add custom dimensions and metrics in the explorations. Now it is even possible to add custom dimensions and metrics to your custom reports.

Under Reports > Library > Create new report > Create detail report you see the list of available custom fields.

New Date and hour dimensions

There are now some more fields available in GA4 for your custom reports to check your data over time.

So the new dimensions are

Hour = 0–23
Nth Hour = Number of hours after the start of the selected date range
Date + hour = Format: 2022120512
Week = 1–53 (week starts on Sunday)
Month = 1–12

Number of pageviews during the day (hourly steps)

Google Tag Manager

Compress Traffic

New server-side containers are compressing network traffic by default now. This change improves the latency of your tagging infrastructure.

Guide for Cloud Run server-side tagging implementation

Google offers two standard ways to implement your server-side tracking infrastructure in their Cloud. It started with the focus of using the App Engine service for it and now Cloud Run comes more and more to the game also.

There is also an official guide available now to set up your server-side tracking environment in Cloud Run.

Upcoming datadice blog posts for this month

Further Links

This post is part of the Google Data Analytics series from datadice and explains to you every month the newest features in BigQuery, Data Studio, Google Analytics and Google Tag Manager.

Check out our LinkedIn account, to get insights into our daily working life and get important updates about BigQuery, Data Studio and marketing analytics

We also started with our own YouTube channel. We talk about important DWH, BigQuery, Data Studio and many more topics. Check out the channel here.

If you want to learn more about how to use Google Data 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.

Originally published at https://www.datadice.io.