LinkedIn
Twitter
We recently held the Google Data Cloud & AI Summit, where top minds in data and AI came together to share expert insights, new solutions, and strategies to help you transform customer experiences with modern apps, boost revenue, and reduce costs.
In this article, we share a summary of product updates and announcements from the Summit, including a roundup of resources to learn more and get started.
Have questions or feedback? Leave a comment below. We’d love to hear from you!
Product updates and announcements from the Google Data Cloud & AI Summit
During the Google Data Cloud and AI Summit, we shared innovations to unlock the value of data and applications. Check out our featured updates below!
BigQuery editions
BigQuery editions provide more choice and flexibility for you to select the right feature set for various workload requirements. You can mix and match among Standard, Enterprise, and Enterprise Plus editions to achieve the preferred price-performance by workload. Along with editions, we’re announcing autoscaling capabilities that ensure you only pay for the compute capacity you use, and a new compressed storage billing model that is designed to reduce your storage costs.
Check out the FAQs, pricing information and product documentation, and register for the upcoming BigQuery roadmap session on April 5, 2023 to learn more about BigQuery’s latest innovations.
AlloyDB Omni
We’re excited to announce the technology preview of AlloyDB Omni, a downloadable edition of AlloyDB designed to run on-premises, at the edge, across clouds, or even on developer laptops. AlloyDB Omni offers the AlloyDB benefits you’ve come to love, including high performance, PostgreSQL-compatibility, and Google Cloud support, all at a fraction of the cost of legacy databases.
See what’s new and next in Google Cloud databases from the Data Cloud & AI Summit session here and learn how to accelerate your move to Google Cloud with the new Database Migration Program.
Looker Modeler
Looker Modeler (available in preview in Q2) is a new stand-alone metrics layer from Looker that enables users to create a single source of truth for their business, and consistently apply those metrics in their existing environment, enabling faster insights and collaboration.
To learn more about Looker Modeler, watch our session from the Data Cloud & AI Summit: Trusted Metrics Everywhere. To test Looker Modeler in your environment, sign up here.
Generative AI
If you’ve been exploring recently-launched consumer generative AI tools like Bard and thinking about how to build similar experiences for your business, Generative AI App Builder, or Gen App Builder for short, is here to get you started.
Gen App Builder is part of Google Cloud’s recently announced generative AI offerings and lets developers, even those with limited machine learning skills, quickly and easily tap into the power of Google’s foundation models, search expertise, and conversational AI technologies to create enterprise-grade generative AI applications.
To learn more, see the Data Cloud & AI Summit sessions from the AI innovation track, as well as the blogs, Build new generative AI powered search & conversational experiences with Gen App Builder and Your guide to Generative AI support in Vertex AI.
Take a step forward to getting hands-on and join the waitlist for our trusted tester program. And finally, bookmark our generative AI landing page to keep abreast of the latest news, updates and possibilities from this exciting new world of Gen Apps.
What’s next: Learning, roadmaps, resources, and early access
Here, we’re rounding up all the helpful resources and next steps coming from the Google Data Cloud & AI Summit, including Cloud Blogs, learning paths, and more.
Dive deep into product announcement blogs
See the latest product announcement blogs listed below and stay tuned on the Cloud Blog for future updates.
- Google Cloud brings generative AI to developers, businesses, and governments
- Solving for the next era of innovation and efficiency with data and AI
- Build new generative AI powered search & conversational experiences with Gen App Builder
- Introducing Looker Modeler: A single source of truth for BI metrics
- Run AlloyDB anywhere - in your data center, your laptop, or in any cloud
- How do I start using AlloyDB Omni?
- New BigQuery editions: flexibility and predictability for your data cloud
- Google Cloud and NVIDIA bring next-generation AI infrastructure and software for large scale models ...
- Your guide to Generative AI support in Vertex AI
- Secure and privacy-centric sharing with data clean rooms in BigQuery
- Google Cloud Contact Center AI reimagines the customer and agent experience
- Announcing new BigQuery inference engine to bring ML closer to your data
Data Cloud & AI Summit ‘23 Resources
Hands-on labs, demos, reports, whitepapers, ebooks, videos, webpages, and more
Join the Google Cloud Trusted Tester Program
The Trusted Tester Program is a place where people can learn about, experience, and give feedback on Google Cloud’s emerging AI technologies. If you’re interested in early access, please join the waitlist. We appreciate your excitement and patience as we expand access.
24/7 access to product roadmaps for Google Cloud customers
Did you know? You can stay informed and up-to-date with 24/7 access to Google Cloud product roadmaps through the Google Cloud Community (where you are now!). Access is only available to Google Cloud customers under NDA. Sign up using this request form: https://goo.gle/gcp-roadmap-request
Start your learning journey with Data and AI
From learning how AI can power your contact center to empowering your frontline workers with the newest technologies, we've created the following learning paths, available on Google Cloud Skills Boost, to help you grow your data and AI/ML cloud skills to transform your career and organization.
And don’t miss our live session on April 5th! Guide to Preparing for the Google Cloud Professional Data Engineer Certification
A Data Analyst gathers and analyzes data to identify trends and develops valuable insights to help solve problems and inform business decisions. They have skills in data cleansing, visualization, and analysis including an understanding of data ethics and tooling.
A Data Engineer designs and builds systems that collect and transform the data used to inform business decisions.
Database Engineer Learning Path
A Database Engineer designs, plans, tests, implements, and monitors database migrations.
Machine Learning Engineer Learning Path
A Machine Learning Engineer designs, builds, productionizes, optimizes, operates, and maintains ML systems.
Join the conversation in the Data Analytics and AI/ML Communities
Join thousands of your peers, Googlers, and industry professionals in our Data Analytics and AI/ML Community forums. This is where you can ask questions, receive answers, and stay up-to-date on the latest innovations in data analytics and AI/ML. See you there!