Google Cloud and Rakuten Cloud are developing a joint solution empowered by AI to tame the stateful edge across several industries. Learn how our joint offering integrating Rakuten Cloud-Native Storage with GDC is transforming edge deployments where issues such as data sovereignty, network uptime, latency and compliance are paramount. We will also discuss a customer use case of integrating cloud-native storage with GDC Edge to meet the needs of mission-critical stateful applications across an organization with thousands of locations.

This Session is hosted by a Google Cloud Next Sponsor.
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In today's rapidly evolving digital landscape, modernizing mainframe systems is crucial for maintaining competitive advantage. This joint solution explores the transformative potential of migrating data warehouse extracts to Google Cloud Platform (GCP) and BigQuery. Utilizing the flexible framework built, organizations can achieve a flexible, integrated solution that accelerates time to market, ensures accurate and timely real-time data for reporting and advanced analytics, and provides self-service access. This digital transformation not only empowers stakeholders with enhanced capabilities but also significantly improves the overall customer experience.

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.

Leveraging real-time data in AI and machine learning (ML) can give you a competitive edge. This session explores how Shopify and Palo Alto Networks leverage real-time data and AI with BigQuery and Dataflow ML to transform customer experiences and drive innovation. Discover how these companies collect, process, and analyze real-time data to achieve significant business outcomes, and learn how to apply similar strategies in your organization.

This session demonstrates how BigQuery ML connects all your data to cutting-edge AI using familiar SQL. Learn practical steps to build, train, and deploy machine learning (ML) models for predictive analytics directly in BigQuery while minimizing complexity and data movement. Discover ways to perform tasks such as sentiment analysis, audio transcription, and document classification with the latest models from Gemini, Claude, Llama, and others directly in BigQuery without the need for advanced Python or specialized ML skills.

Business intelligence professionals and data practitioners, join us to share experiences and brainstorm solutions to your biggest data challenges. Whether you're tackling AI hallucinations, accelerating large queries, or defining data governance, this meetup provides a space for interactive discussion with peers and data experts. Bring your own topics to explore real-world scenarios and grow your network within our community.

Agencies are applying cutting-edge technology to safeguard communities and resources, bolster emergency management, and streamline disaster response efforts. Learn how AI, predictive capabilities, real-time data analysis, and a modernized IT infrastructure can be used to build a more resilient future.

Integrating data from Oracle ERP to Google BigQuery? Join this session and discover how to enable seamless data integration, creating a robust data and integration fabric on Google Cloud. This capability enhances data accessibility and analytics, empowering informed business decisions. We also developed an abstraction layer to streamline integrations, fostering synergy across third-party platforms, accelerating time-to-value, and supporting a scalable, data-driven enterprise.

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.

Are you ready to get hands-on with Google Cloud’s AI tools? In this 2 hour gHack, you will work in teams of 4. Together you will build a Formula E Race Analysis System from scratch using a variety of our AI and Data tools. Teams will work together to build the solution by searching, learning and collaborating together to find the answers needed. 3-2-1 lights out and away we go!

This session will cover how to optimize remote sensing data analysis using Ray, Kubeflow, and Google Cloud Platform (GCP). Learn how to leverage distributed computing, orchestration workflows, and xarray for efficient processing of geospatial data from Unmanned Aerial Systems (UAVs), LiDAR (Light Detection and Ranging), and Ground Penetrating Radar (GPR). Attendees will gain practical insights into building scalable, cloud-native pipelines that accelerate data processing and deliver faster, more actionable insights.

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!

Geographical redundancy is a key pillar of a resilient data architecture. With BigQuery cross-region dataset replication and managed disaster recovery, you can ensure your mission-critical apps remain available even in the unlikely event of a region-level infrastructure outage. Learn how this built-in capability protects your data and workloads against regional outages and ensures uninterrupted data access for your organization.

Join Deutsche Bank and Deloitte as we show you how our GenAI-powered chatbot is enhancing customer engagement, driving efficiency, and changing the face of banking. In this fascinating session, we'll demonstrate how the chatbot, integrated into the Deutsche Bank customer-facing banking app, provides accurate product and service information, guides customers to the right transactions, and seamlessly connects to live agents as needed. We'll also review insights and best practices for implementing your own chatbot solutions on 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.

See how a small team can leverage Google Cloud to serve millions. As the former lead of Flutter and mobile-specialist, I started with little knowledge of Cloud. Using Google's Dart and Google Cloud, we've built a successful service across Cloud Run, Compute Engine, Big Query, Storage, CDN and more and here to share our learnings.

Are you ready to get hands-on with Google Cloud’s AI tools? In this 2 hour gHack, you will work in teams of 4. Together you will build a Formula E Race Analysis System from scratch using a variety of our AI and Data tools. Teams will work together to build the solution by searching, learning and collaborating together to find the answers needed. 3-2-1 lights out and away we go!

Discover how to break free from the cycle of endless AI Proofs of Concept (POC) and unlock scalable, enterprise-wide impact. In this session, we’ll explore proven strategies for operationalizing AI, including leveraging cloud-native solutions like Vertex AI, building robust MLOps pipelines, and defining measurable ROI tied to business goals. Through real-world examples and actionable insights, learn how to overcome common scaling challenges, drive cultural adoption, and future-proof your AI strategy for sustained innovation and 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.

Building product recommendation system/chat bot using LLMs is simple... on paper. In reality, simple RAG covers only the simplest scenarios. To cover more complicated one, you may want to learn about such things as a conversation graph, logical and semantic routing, hybrid search etc. In this talk I share lessons and tricks we have learn during building product recommendation system using Gemini.

Small teams often struggle to unlock the full potential of their data due to limited resources and a lack of specialized expertise. In this session, we’ll show you how BigQuery and Looker make advanced analytics accessible and easy for teams of any size. Learn how to seamlessly integrate, analyze, and visualize your data to drive data-driven decisions and achieve your business goals.

This session provides a comprehensive guide to building a secure and unified AI lakehouse on BigQuery with the power of open source software (OSS). We’ll explore essential components, including data ingestion, storage, and management; AI and machine learning workflows; pipeline orchestration; data governance; and operational efficiency. Learn about the newest features that support both Apache Spark and Apache Iceberg.

This session explores the business drivers for ESG data in the current business climate and delves into the technical architecture of a robust ESG data management solution. Discover how to integrate AI and data agents with core enterprise systems, like SAP and Cortex, and incorporate crucial third-party ESG data from sources like ESG Book to enhance business decision-making. We will also showcase real-world examples of how to integrate Google Cloud with platforms like Watershed to build a complete ESG data ecosystem. 

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.

Are you a data scientist or developer using Python to build AI models and generative AI applications? Learn how BigQuery can supercharge Python data science workflows with capabilities that give you the productivity of Python and allow BigQuery to handle core processing. Offloading Python processing enables large-scale data analysis and seamless production deployments along the data-to-AI journey. Find out how Deutsche Telekom modernized their machine learning platform with a radically simplified infrastructure and increased developer productivity.