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, Dataform, 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, Dataform, Looker Studio, Google Analytics & Google Tag Manager.
BigQuery
Error handling support with Gemini
Gemini now offers even better support for your SQL coding. You can use it to fix errors either before or after running your query.
Before execution: Highlight the problematic code and select Refine > Fix it. A chat window will appear with a suggested solution. Simply click Apply to update the SQL code.
After execution: If BigQuery shows an error, click the "Gemini suggested fixes" button. The chat will open and explain the fix. Clicking Apply & Run automatically updates the code and re-executes the query.
JSON_FLATTEN function
This new function does exactly what its name implies: it flattens the JSON data passed as the first parameter.
The function recursively traverses a JSON object (even through arrays) and extracts all leaf nodes. It effectively transforms a hierarchical tree structure into a flat list of values.
SELECT JSON_FLATTEN(JSON '[[[[1], 2], 3], {"earth": 3}, false]') AS json_flatten
Use Gemini 3.0 in generative AI functions
BigQuery got a lot of easy-to-use AI functions for your SQL Code. Some of them I explained in our last blog post.
Furthermore, you probably heard about the new Gemini 3.0. The new, most powerful version of Gemini.
Gemini 3.0 is not the default version for the AI functions yet. To use it, you need to define the endpoint in the function. The corresponding endpoint URL is (The project ID needs to be replaced):
https://aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/global/publishers/google/models/gemini-3-pro-preview
Then you can do the following:
SELECT
title,
movie_url,
review,
AI.CLASSIFY(
review,
categories => ['negative', 'neutral', 'positive'],
connection_id => 'us.vertex_ai_us_connection',
endpoint => 'https://aiplatform.googleapis.com/v1/projects/datadice/locations/global/publishers/google/models/gemini-3-pro-preview') AS category
FROM `bigquery-public-data.imdb.reviews`
BigQuery ML changes
BigQuery ML supports the TimesFM 2.5 time series foundational model now.
Additionally, it supports a lot of AI functions now:
- AI.DETECT_ANOMALIES
- AI.GENERATE_EMBEDDING
- AI.GENERATE_TEXT
- AI.GENERATE_TABLE
- AI.GENERATE_BOOL
- AI.GENERATE_DOUBLE
- AI.GENERATE_INT
- AI.SIMILARITY
- AI.EMBED
- AI.GENERATE
Other changes
- Folders can be created in BigQuery to organize saved queries, canvases, notebooks, and more
- The query execution graph is able to show a query text heatmap. Further information can be found here
- The following SQL dialects can be translated to GoogleSQL: Apache Impala SQL and GoogleSQL. Translation of GoogleSQL can be used for improvements of the translated code from another dialect
- A new BigQuery Agent Analytics plugin in the ADK is available to export the data from the agent interactions to BigQuery. Further information can be found here
Dataform
Small Changes
Google just released minor improvements to Dataform:
- Support for custom constraints to allow better control over resources like "CompilationResult" or "WorkflowInvocation"
- Creation of BigLake tables for Apache Iceberg in BigQuery
Looker Studio
Conditional Formatting on bar charts
Conditional formatting is now available for bar charts. You can choose between two types:
- Rules: Change colors based on specific criteria
- Gradients: Adjust color intensity based on the value
With the Rules type, you can customize the appearance of bars and data labels. If you apply the rule to the entire row and the condition is met, all bars associated with that dimension are colored accordingly.
The remaining settings are identical to those for tables.
Cloud Audit Logs (Pro)
Information about administrative activities and data access is logged automatically and can be viewed in the Logs Explorer of the corresponding Google Cloud Project now. Logged events include:
- Permission Management
- Ownership Transfers of dashboards or data sources
- API calls
In the Logs Explorer, you can find the logs under "Audited resource":
Parameters as default values in filters
Parameters are a good opportunity to build a more complex dashboard with the help of the user's input.
You can use the parameter now to define the standard value of a filter. The value of the parameter is used then, when the user did not choose a value for the filter.
As shown in the screenshot below, the parameter can have a default value as well, which is used in the filter too.
Google Analytics
User-provided data improvements
You can send additional user data (like email or name) to Google Analytics to enable more reliable user analysis.
Google has improved the analysis capabilities of this feature to deliver better performance, specifically:
- A focus on activation and Ads Conversions
- Improvements to Enhanced Conversions and Customer Match Audiences
- More accurate attribution and event reporting
Additionally, Google launched a new UPD infrastructure. This is currently used for customers who start sending UPD data. Customers with existing UPD setups will be migrated to the new infrastructure in Q2 2026.
Google Tag Manager
No further release for Google Tag Manager.
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, Looker Studio, and marketing analytics.
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 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.
