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Confidential Space, which allows organizations to perform tasks such as joint data analysis and machine learning (ML) model training while having trust guarantees that the data they own can stay protected from their partners and the cloud service provider.

Security announcements aim to progress the goal of making security more proactive by the use of automation and other tooling.

Plans to bring new Google Cloud regions to Austria, Greece, Norway, South Africa, and Sweden, in addition to the already announced plans for Malaysia, Mexico, New Zealand, and Thailand, bringing the global network to 48 live and pending regions.

Introduction of the OpenXLA Project, a consortium alongside contributors including ARM, Intel and Nvidia which aims to reduce the cost and complexity of ML development by creating ML frontend frameworks that are tuned to work with various hardware backends for faster, more flexible development.

The capability is built on top of technology initially developed by Banco Santander.

Dual Run, which allows customers to make a digital copy of their mainframe system and run it simultaneously on Google Cloud to complete regulatory and compliance testing prior to retiring the original mainframe.

A new C3 virtual machine family which runs on the 4th Gen Intel Xeon Scalable processor and the custom Infrastructure Processing Unit (IPU) that Google co-designed with Intel.

Improvements to the underlying Google Cloud infrastructure include: Expanding integrations with leading enterprise data platforms, including Collibra, Elastic, MongoDB, Palantir Foundry, and ServiceNow.The launch of Vertex AI Vision, a new service that makes powerful computer vision and image recognition AI more accessible to data practitioners.Partnerships with Tableau and Microsoft Power BI allow API access to Looker data in these third-party tools.

Google Data Studio becomes Looker Studio as part of a deep integration of Looker, Data Studio, and AI and machine learning (ML) technologies.Updates to Dataplex for automated data quality and data lineage processes.Extending the BigLake storage engine to include support for major data formats such as Apache Iceberg, Linux Foundation Delta Lake and Apache Hudi, as well as a new integrated experience in BigQuery for Apache Spark.A new integration between Datastream and BigQuery to help organizations replicate real-time data from various external data sources directly into BigQuery.Adding support for unstructured data in BigQuery, bringing in sources such as video, audio and documents for analysis alongside the more structured operational and time-series data it has traditionally supported.On data, Google is working towards offering what it calls an open Data Cloud, able to support all kinds of workloads and all styles of analysis. Removing barriers to collaboration is the final big theme, with new capabilities in Workspace. Allied to this is the second big theme of security, with several announcements offering more granular and proactive security measures. Inevitably, data is a huge part of the story, in particular breaking down data silos so that enterprises can work across all of their data, with announcements around opening up access to data and expanding the reach of BI and AI. Three themes cut across the usual flurry of product announcements at this year's Google Cloud Next conference, which opens later today.