Google, at the Google Next conference, announced many different changes to simplify the lives of Analytics Engineers massively. What is important for users of my website is that DBT is now integrated with BigQuery DataFrames, and DBT Cloud is now on Google Cloud.

The good news for all analytics engineers is that BQ now supports building data pipelines with new preview options built into it to maintain quality and automate metadata generation. Something that confuses me a bit is that BigQuery allows you to apply operators in any order and as often as you need, and is compatible with most standard SQL operators. Does it mean that someone who will start from BQ will struggle with moving to a different platform because of the SQL syntax? Not sure. Especially that now BQ has AI code assist capabilities, enabling you to use natural language prompts to generate or suggest code in SQL or Python, or to explain an existing SQL query. New SQL translation assistance lets you create Gemini-enhanced rules to customise SQL translations. 

BQ added many great additions based on AI, including Gemini to analyse schema relationships, table descriptions, and query histories to generate metadata on the fly, model data relationships, and recommend business glossary terms. It allows processing structured and unstructured data together, which will speed up business action. 

I think that people in all geospatial data, including Telco, are happy with the announcements of integration of Google Maps Platform datasets directly into BQ, which, in addition to Earth Engine, brings the best of Earth Engine’s geospatial raster data analytics directly into BigQuery.

Regards the data governance and cataloging,g BQ can now perform automatic at-scale cataloging of BigLake and object tables and enables bulk extract of catalog entries into Cloud Storage. The new feature contribution analysis helps you pinpoint the key factors (or combinations of factors) responsible for the most significant changes in a metric, and the new BigQuery universal catalog brings together a data catalog (formerly known as Dataplex Catalog) and a fully managed, serverless metastore, now generally available.

But there is so much more that I am not even trying to explain here, as I already copy and paste the majority of the information directly from the Google website: https://cloud.google.com/blog/topics/google-cloud-next/google-cloud-next-2025-wrap-up so please simply head there for more information