Discover how TELUS centralized 14 petabytes of data in Google Cloud, creating a single source of truth for AI innovation. Join us to explore how they transformed hundreds of enterprise-grade pipelines and get insights into responsible AI practices and future plans.

This hands-on lab guides you through importing real-world data from CSV files into a Cloud SQL database. Using a flight dataset from the US Bureau of Transport Statistics, you'll gain hands-on experience with data ingestion and basic analysis. You'll learn to create a Cloud SQL instance and database, effectively import your data, and build a foundational data model using SQL queries.

If you register for a Learning Center lab, please ensure that you sign up for a Google Cloud Skills Boost account for both your work domain and personal email address. You will need to authenticate your account as well (be sure to check your spam folder!). This will ensure you can arrive and access your labs quickly onsite. You can follow this link to sign up!

Lean teams often struggle to manage the overwhelming volume of unstructured content. This session explores how Gemini, Google’s cutting-edge AI, can help you easily structure and analyze this data. Learn how Box AI is utilizing Gemini with their customer solutions, and examine a real-world use case from Fundwell. Get insights on how to automate data extraction, enhance customer interactions, streamline operations, and gain a significant competitive edge. Discover how AI can empower your team to unlock the true value within your data.

Join this Cloud Talk to explore how Large Language Models (LLMs) can revolutionize your data workflows. Learn to automate SQL query generation and stream results into Confluent using Vertex AI for real-time analytics and decision-making. Dive into integrating advanced AI into data pipelines, simplifying SQL creation, enhancing workflows, and leveraging Vertex AI for scalable machine learning. Discover how to optimize your data infrastructure and drive insights with Confluent’s Data Streaming Platform and cutting-edge AI technology.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

App life cycles with Google Cloud databases and runtimes have gotten smarter. This session takes you through the life cycle of building and optimizing scalable, high-performance generative AI apps. We’ll use Google’s latest natural language and vector search technologies to build the “art of the possible” for AI-powered software. We’ll also cover various app design patterns using Gemini Code Assist, foundation models, agentic retrieval-augmented generation (RAG), and orchestration frameworks, and show you how it all comes together in a live demo.

Drive the next wave of AI innovation with Google Cloud databases. This Spotlight session explores cutting-edge innovations that enable you to modernize your database estate to quickly build gen AI apps, unify transactional and analytical workloads for real-time insights, and simplify database management with assistive AI. Join us to witness the future of Google Cloud databases, exclusive product announcements, insightful demos, and inspiring customer stories.

Mayo Clinic Platform (MCP) will share their experience building an Internal Developer Platform (IDP) and how it has significantly accelerated developer onboarding and deployment to their network, including the Mayo Clinic Care Network (MCCN) when hosted. This platform has been a key driver in rapidly delivering innovation, which has historically been challenging in healthcare. Eviden played a crucial role as a key partner in the initial development, and MCP is progressively taking on more internal ownership to support future scaling and growth.

Generative AI enables you to build amazing new apps, but you may also have concerns. Will it be too complex or too expensive, or will it create security risks? Fortunately, building good gen AI apps has become much easier in the past year, in large part due to updated capabilities within databases. We’ll learn how Google Cloud databases handle key AI technologies like vector search, retrieval-augmented generation (RAG), and orchestration, helping you bridge the gap between general-purpose AI models and your business-specific data. We’ll dive into some fun application examples to see how they were built and how you can use the same techniques in your apps.

Cloud infrastructure's scale makes backup challenging. Traditional methods, relying on manual tagging and costly snapshots, fall short. Eon, a next-gen backup platform, provides autonomous cloud backup posture management with instant data access. Join this session to learn how Eon continuously maps and classifies resources across multi-cloud environments, applying backup policies based on requirements—no tagging needed! See how Eon's globally searchable backups enable instant restoration without full restores, finally making backups useful.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

Discover the power of Google Cloud’s fully managed, horizontally scalable relational database service—Cloud Spanner. In this hands-on lab, you'll gain practical experience in performing essential administrative tasks within a Cloud Spanner instance. Learn how to create instances and databases, design tables, insert and modify data, and leverage the Google Cloud CLI and automation tools for efficient management.

If you register for a Learning Center lab, please ensure that you sign up for a Google Cloud Skills Boost account for both your work domain and personal email address. You will need to authenticate your account as well (be sure to check your spam folder!). This will ensure you can arrive and access your labs quickly onsite. You can follow this link to sign up!

Simplify database management with Database Center. This generative AI-powered solution provides a centralized view of your entire database fleet, helping you monitor availability, security, compliance, and data protection. In this session, you’ll learn how to easily detect performance issues, visualize granular metrics, and get AI-powered recommendations for optimization. You’ll also discover how customers are streamlining their database operations and boosting efficiency with Database Center.

This session showcases an end-to-end generative AI application on Google Cloud. We’ll demonstrate how to use Gemini 2.0 Flash to analyze user-uploaded images, extract features, and generate descriptions stored in AlloyDB. Then we’ll show you how to fine-tune Gemini 2.0 Flash with BigQuery and generate outfit recommendations with AlloyDB low-latency querying. Finally, we’ll use the output from Gemini 2.0 Flash and Imagen 3 to create visuals of the outfits and deploy the entire solution on Cloud Run.

Google brings together the scalability, reliability and ease-of-use of Firestore with MongoDB compatibility. The session will showcase Firestore with MongoDB compatibility and its capabilities. In addition, Mayo Clinic will present their use of Firestore for multiple workloads including using Firestore’s GenAI capabilities for delivering personalized experiences in their applications. 

Grupo Pavisa plans to revolutionize its business model by basing decisions on a single source of truth using RISE with SAP on the Google Cloud Platform. Learn how this transformation will reduce delivery times, improve production capabilities and enable the creation of better forecasting models. Join Luis Gabriel Martínez from Grupo Pavisa and Clay Caldwell from Kyndryl for a discussion of how a pragmatic approach to modernization and co-creation with Kyndryl, SAP and Google is enabling success.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

This session presents Schnucks’, a midwest grocer’s migration of their E-commerce application from Oracle Database to Cloud SQL PostgreSQL. It will cover challenges such as addressing the complexities of even "simple" schemas, testing data movement possibilities to minimize downtime, and transforming the database tier. Hear about the business impact, including cost savings, increased database-application proximity and the potential for similar future migrations, allowing for direct integration options from Google CloudSQL to Google Gemini AI.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

Discover how MasOrange together with Kyndryl is simplifying operations and reducing costs by migrating workloads to Google Cloud Platform . This session highlights key strategies, including leveraging enterprise agreements for savings, optimizing cloud costs through technical decision-making, and enabling self-service capabilities for developers. Learn how to enhance application performance, streamline infrastructure, and tackle challenges in a smooth, secure and transparent migration journey to Google Cloud.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

Level up your Java apps with the power of Gemini. This session explores how Java developers can easily integrate generative AI features into their applications using LangChain4j. We’ll cover everything from building chatbots and implementing in-context learning to creating agentic workflows and using advanced techniques like unstructured data extraction. Learn best practices and build smart, AI-powered Java applications with ease. No Python experience required.

Google's Data Cloud is a unified platform for the entire data lifecycle, from streaming with Managed Kafka, to ML feature creation in BigQuery, to global deployment via Bigtable. In this talk, we’ll give you a behind the scenes look at how Spotify's recommendation engine team uses Google's Data Cloud for their feature pipelines. Plus, we will demonstrate BigQuery AI Query Engine and how it streamlines feature development and testing. Finally, we'll explore new Bigtable capabilities that simplify application deployment and monitoring.

This session brings together leading product experts from Google Cloud, Anthropic, Oracle, Databricks, and SAP to explore the five essential strategies for enterprises to successfully leverage AI and data. Attendees will gain valuable insights from real-world AI implementations, learn from the successes and challenges faced by global customers, and receive practical guidance on how to translate these strategies into actionable plans for their own AI journeys.

Discover how semiautonomous agents reduce manual effort and accelerate business outcomes with AI-powered experiences for data discovery, data preparation, analysis, and insight generation.