Traditional approaches and thinking around data quality are out of date and not sufficient in the era of AI. Data, analytics and AI leaders will need to reconsider their approach to data quality going beyond the traditional six data quality dimensions. This session will help data leaders learn to think about data quality in a holistic way that support making data AI-ready.

To position their teams as a must-have discipline that can fulfill cross-functional use cases, D&A leaders must optimize their organizational model. The optimal organizational model is one that balances enterprisewide capabilities focused on enablement with decentralized needs focused on outcomes. In this session you will learn the design principles behind the right D&A organizational model and how to balance a centralized team (focused on enablement) and decentralized needs (focused on outcomes).

In this session, we will explore DeepSeek’s transformative impact on AI development, highlighting its potential to enhance enterprise innovation at a price/performance that is unprecedented. Data, analytics & AI leaders can bring their questions on how they can capitalize on new training and inferencing paradigms in AI, the future of AI model development and the impact of reasoning models on a more autonomous future in AI.

Modernize your analytics capabilities by identifying the products that best meet your needs. See side-by-side, scripted demonstrations of three leading vendors: Strategy, Oracle and Tableau. What are the key features to consider and how do they compare in action? What are the main strengths and weaknesses of these vendors? What innovations are coming?

Data and analytics leaders need to support the opportunities and challenges of today’s digital business with the right competencies. This is the time to evaluate data and analytics roles and skills that are fit for now and the future. This session will provide key considerations for D&A and AI roles and skills.

Find out about the emerging, most hyped and ready for prime-time concepts and technologies in data, and analytics, and AI programs and practices.

How can data science accelerate the energy transition? In this session, UK Power Networks’ Data Science team presents real-world tools driving a smarter, more flexible electricity grid on the path to Net Zero. From democratising access to grid insights to automating decision-making for clean energy, this talk highlights how applied AI and analytics are transforming infrastructure at scale, with lessons for any data professional tackling high-impact, real-world problems.

Learn about proven techniques to boost the use and productivity of your self-service analytics environment. What works and what doesn't? What should you prioritize if you're just getting started? How can you keep the environment fresh as you mature? What should you be thinking about in addition to analytics as you build and grow your approach? Join us to know the answers to such questions.

While AI is popular in the media, surveys show about half of organizations struggle with basic data science, fearing they will fall behind. This fear can hinder progress, especially in certain industries. However, they don't have to choose between AI and foundational data science. By combining predictive and prescriptive analytics, organizations can leverage the best of both worlds to create better solutions.

To support its Digital First mission, the BBC is transforming into a data product organisation. This session will explore how the BBC's data strategy is driving a cultural and organisational shift that is evolving its data architecture and embedding data capabilities company wide. Discover the BBC's approach to developing certified, shareable data products that strengthen governance, enable self-service analytics, and establish a foundation for responsible AI use.

Join us to hear from Oracle Red Bull Racing and learn about the Oracle and Oracle Red Bull Racing partnership, highlighting the significance of how Oracle technology is the backbone of success to the Championship winning Formula 1 team. Oracle is supporting the build of the 2026 Powertrain engine and how analytics from the race simulator is helping form the next generation of drivers.

Decision intelligence is quickly gaining traction as the discipline that aims to connect analytics and decision making. But how to make decision intelligence a reality? Where to start, which approach to follow, how to go about the reengineering and modeling of decisions and which decision intelligence platforms are available? This session will address these and other emerging practices to improve your business impact.

Tableau Next is built on the Salesforce Platform - a unified platform where data, metadata, workflows, apps, and AI come together to make agentic analytics possible. Join this session to learn more.

CDAOs implement self-service analytics (SSA) to enable data-driven decision making across their organizations. However, SSA initiatives often fail to deliver on their full potential due to governance, trust, scalability and adoption challenges. This presentation provides a framework for CDAOs to balance control and agility within SSA to drive meaningful business value from data.

Data catalogs suffer from a high failure rate that is often blamed on poor technology choices but are more often the result of nontechnical issues. This session will provide insight to data and analytics leaders in evaluating metadata management requirements, assessing readiness of organizations and best practices for getting started to implement a data catalog.

Data is the fuel for Oracle Red Bull Racing to analyze their practices and qualifying races. By using a modern technology stack on Oracle, the Oracle Red Bull team was able to increase the number of simulations it could run, allowing the team to explore more variables and increase accuracy by focusing on track conditions, the pace of the car, and tire degradation to evolve the team’s strategy. Focusing on competitor analysis also helps determine how to navigate rival strategies that give our drivers the best chance to win.

Discover how you can implement a winning data & analytics solution.

Data and analytics leaders must operate within the realities of the geopolitical impacts that we now face. These include an increased focus on contingency planning for diverse vendor selection, avoid reliance on products or technologies that may be subject to trade policies or other restrictions and confronting increased costs.

Join us to explore how AWS is shaping the future of data and AI, unlocking new opportunities for business innovation and data driven decision-making with the next generation of Amazon SageMaker, your center for data, analytics, and AI. Collaborate faster with proven services coming together in a unified experience, with open access to all your data and with built-in governance.

The days of running a business on Excel and static reports are long gone. Organizations need to be more agile than ever before, and AI can help transform not only what you do but take you to the next level and drive adoption and value. Join Pyramid Analytics and their premier customer East of England Co-op, and learn how they reinvented their data and analytics strategy. They'll share the tangible steps they took to conquer their challenges, the benefits they are seeing today, and their exciting path forward with AI and analytics!

Data teams face pressure to deliver real-time business insights across finance, supply chain, HR, and beyond. They need apps that are fueled with AI recommendations and insights available in business terms. The key lies in adopting a business data fabric architecture that interoperates across multi-cloud landscapes. SAP’s data and analytics solutions serve as the foundation for this data fabric, delivering an integrated, semantically-rich data layer that ensures seamless and scalable access to data without duplication. Join us to learn how to build this crucial foundation for your AI applications.