Join Virgin Media O2 and Google for a technical discussion about lessons learned and best practices for building and scaling a data fabric on BigQuery. Find out how Virgin Media O2 eliminated silos and enabled secure and governed data sharing at scale to drive better decisions and get more value from their data.

Generative AI and machine learning (ML) are transforming industries, but many smaller organizations believe these technologies are out of reach due to limited resources and specialized skills. In this session, we’ll demonstrate how BigQuery is changing the game, making gen AI and ML accessible to teams of all sizes. Learn how BigQuery – with its serverless architecture, built-in ML capabilities, and integration with Vertex AI – empowers smaller teams to unlock the power of AI, drive innovation, and gain a competitive edge.

The rise of AI demands an easier and more efficient approach to data management. Discover how small IT teams are transforming their data foundations with BigQuery to support AI-powered use cases across all data types – from structured data to unstructured data like images and text (multimodal). Learn from peers across industries and geographies why they migrated to BigQuery and how it helped them accelerate time to insights, reduce data management complexity, and unlock the full potential of AI.

Get the inside story of Yahoo’s data lake transformation. As a Hadoop pioneer, Yahoo’s move to Google Cloud is a significant shift in data strategy. Explore the business drivers behind this transformation, technical hurdles encountered, and strategic partnership with Google Cloud that enabled a seamless migration. We’ll uncover key lessons, best practices for data lake modernization, and how Yahoo is using BigQuery, Dataproc, Pub/Sub, and other services to drive business value, enhance operational efficiency, and fuel their AI initiatives.

Discover how to transition from legacy, siloed systems to a unified, scalable, and insights-driven data platform on GCP. This session will cover best practices for data migration, overcoming common challenges, and integrating SaaS and third-party solutions using key Google Cloud services like BigQuery, Data Fusion, Cloud Storage, Application Integration, Cloud Run, Cloud Build, and Artifact Registry.

This Session is hosted by a Google Cloud Next Sponsor.
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Unleash the power of AI-driven analytics with Gemini and BigQuery. Learn how to uncover trends, automate complex queries, and make smarter decisions. Explore real-world examples from industry leaders using AI to extract insights from unstructured data like text, images, and audio to streamline operations and unlock growth.

Is your outdated data infrastructure hindering your ability to leverage the full potential of AI and machine learning? This session explores how migrating to BigQuery can empower you to modernize your data infrastructure and unlock new opportunities for innovation with all of your data. Hear how Paypal and Intesa Sanpaolo transformed their data platform with BigQuery to get the most value from their data lakes and warehouses and the lessons they learned along the way. 

The modern data landscape is exploding with complexity. This session explores AI-first capabilities in BigQuery to simplify the discovery, preparation, and management of data. Learn about BigQuery Studio, BigQuery data canvas, and BigQuery data preparation for data science workloads. Discover how to connect and unify data from various sources for deeper insights and better business outcomes, with examples from Standard Industries, and how to prepare data for analytics and insights with AI-first data tools

Learn how you can use BigQuery and Earth Engine together for a variety of weather and climate resilience use cases including risk assessment, response, and recovery. You'll receive a real world step-by-step walkthrough, highlighting new geospatial features and AI-driven datasets, that make it easier for any professional to unlock insights that can contribute to greater climate resiliency.

Agentic AI is poised to revolutionize how marketing & data teams unite to fuel revenue growth in 2025 and beyond. Join this session to discover how marketers can leverage AI agents applied directly to Google Cloud BigQuery to suggest, build, and execute campaigns that compound over time. You’ll learn how GrowthLoop’s marketing activation solution, built on Google Cloud BigQuery, leverages Agentic AI to automate campaign launches, accelerate experimentation, and deliver hyper-personalized experiences at scale.

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.

Unlock the full potential of your data with the power of AI. This session explores how Google Cloud’s latest advancements in AI are transforming business intelligence, empowering you to gain deeper insights, make faster decisions, and drive innovation. We’ll dive into trusted insights with BigQuery and AI, the power of the Looker semantic layer, and how Google Cloud’s AI-powered business intelligence (BI) solutions can help you transform your data into actionable intelligence and drive business success.

This session dives into the world of on-demand Apache Spark on Google Cloud. We explore its native integration with BigQuery, its new capabilities and the benefits of using Spark for AI and machine learning (ML) workloads. We’ll discuss why Spark is a good choice for large-scale data processing, distributed training, and distributed inferencing. We’ll learn from Trivago about how they leveraged the Spark and BigQuery together to simplify their AI and ML workflows.

This scalable, AI-powered data quality solution requires minimal coding and maintenance. It learns about your data products to improve data quality across multiple dimensions. The framework uses BigQuery, BQML, Dataform, and Looker to deliver a comprehensive and automated Data Quality solution with a unified user experience for both data platform owners and business users.

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.

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.

Build modern applications with the power of Oracle Database 23ai, and Google Cloud's Vertex AI and Gemini Foundation models. Learn key strategies to integrate Google Cloud’s native development tools and services, including Kubernetes, Cloud Run, and BigQuery, with Oracle Database 23ai and Autonomous Database, seamlessly into modern application architectures. Cloud architects, Developers, or DB Administrators will gain actionable insight, best practices, and real-world examples to enhance performance and accelerate innovation with ODB@GC.

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.

In this session, we’ll show how Vertex AI and BigQuery make the process of integrating data into AI models as easy as 1, 2, 3. You’ll learn how to seamlessly integrate your data estate at every stage of AI development, from exploration and feature engineering to model training and deployment. We’ll also introduce our Data Science Agent and Vertex AI Feature Store 2.0, and how you can accelerate your innovation velocity with AI.

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.