BigQuery
Google Search Public Dataset
BigQuery offers a lot of public datasets with data from different topics. Google added a new dataset with Google Search Trends. You can find the dataset here.
The dataset has a lot of data and looks like a great way, to learn BigQuery, write the first SQL Queries and build dashboards.
Slot recommender
Google still tries to help the users of BigQuery to get more insights into the payment behaviour of their BigQuery instances. The slot recommender analyzes your usage of BigQuery and knows your current billing model.
When you use on-demand billing you will get advice if you should switch to flat-rate pricing and how much money you would save. Other insights are also possible for the usage of the resources.
Specify schema for external tables
When you create external tables in BigQuery with Parquet, ORC and AVRO files you can specify the schema now. Before it was just possible to use the auto-detect schema option.
Data Studio
More table rows
Data Studio got a lot of small changes. For example, they increased the possible number of rows of a table on one page from 5.000 to 50.000 rows. I am not sure when you need 50000 rows in a table and also take into consideration that your page load speed decreases with the amount of data you show.
Last possible steps for Rows per page
Default cross-filtering
Another small change, that you should keep in mind, is the change for cross-filtering. With cross-filtering, you can click on a dimensional value in a chart and the report gets filtered for this value.
Filter for the region "San Jose"
Quick Tip: With CMD + Left Click you can select more than one filter value.
From now on the cross-filtering setting is enabled by default for new charts (for most connectors). You should consider when it makes sense to offer that option to the users because it could happen that they click on a Chart by mistake and then the report gets filtered.
Improved homepage search
On the homepage of Data Studio, you can find your reports, templates, data sources and many more. You can also search for them and this search got improved.
- Search for reports you have shared with a person (to: person)
- Reports or Data Sources shared with you (from: person)
- Search by the owner
- Using “me” for your own account
Also, the use of “AND” or “OR” for building a detailed search is also possible.
Google Analytics
End of Universal Analytics
This is not part of the Release Notes from Google Analytics, but I think the biggest announcement in the last weeks. We wrote our own blog post about it, so just a quick summary.
Mid of 2023 the support for Universal Analytics gets stopped and the properties will not collect any data. It is the right time to start with the “new” version of Google Analytics, Google Analytics 4. It is still not the perfect analytics solution, but it is getting better and better. Additionally, there is no way to convert your UA data to GA4 data, so you should start tracking to fill your GA4 properties.
New Home Page for GA4
The new starting point for the GA4 platform is the Home Page. Overall it shows a summary of the behaviour of the users on your website or app. The shown charts and KPIs are adjusting to your behaviour on the platform over time, so for example which reports you are looking at most of the time.
The new GA4 Home Page
Google Tag Manager
Firestore API
Cloud Firestore is a NoSQL, transactional and document-based database in the Google Cloud Platform. It is a strong database, especially for operational usage. With the combination of server-side tracking and Firestore, you can enrich your reporting.
An example would be a purchase on the website. You just send the order id to the GTM and when you use Firestore as your operational database you can get all the additional information you need from Firestore. The steps you have to do in GTM to achieve that, are the following:
- Create a Firestore variable in GTM
- Add the order id from the website to the request
- Define the data you want
- Enrich your tags with the information from Firestore
This is one great example to show the strength of server-side Tracking. It can easily interact with other tools and define the requests on a detailed level.
Upcoming datadice blog posts for this month
- Integrating data sources into a full-stack data platform - here
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