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Analytics and BI are evolving as organizations use unified data to deliver faster, trusted insights. This track covers scalable dashboards, self-service analytics and AI-driven conversational experiences that let users talk to their data, answer questions and uncover insights faster.

Developers are racing to build AI-powered apps on their data, but fragmented tools slow them down. This track covers how to build, deploy and scale data and AI apps with real-time workloads and agentic experiences using familiar tools and streamlined workflows.

AI is transforming how organizations build intelligent solutions. This track covers AI, agents and machine learning, from design to deployment. Learn to build and scale AI agents, manage models in production, evaluate quality and navigate governance, security and compliance.

Data engineering is critical to delivering reliable data for analytics and AI. This track covers best practices for building and scaling pipelines from batch to real-time streaming, and how engineers use AI to accelerate development, improve data quality and automate pipeline operations.

Data sharing and collaboration are driving innovation by enabling secure access to data and AI across organizations. This track covers best practices for sharing data and models across platforms and regions, avoiding replication, monetizing data products and collaborating with partners in a privacy-safe way.

Organizations are entering a new era where data, AI and automation converge. This track explores how leaders align strategy, architecture and operating models to drive real outcomes. Learn how to design accountable AI systems, enable autonomous decisioning and scale data-driven innovation across the enterprise.

Data delivers value when transformed into insights. This track covers modern data warehousing, high-performance SQL and BI. Learn best practices for ingestion, federation and dashboards, along with AI-driven capabilities like natural language queries, performance optimization, governance and observability.

Organizations are rethinking how they govern and secure data and AI across multicloud environments. This track explores unified governance for consistent access, discovery and trust. Learn how to simplify compliance, enforce policies and use AI to automate data quality, monitoring and governance at scale.

Applications, analytics and AI have relied on separate systems, forcing data movement and duplication. This track explores how to unify transactional and analytical workloads to simplify architectures, eliminate data movement and build real-time apps, AI systems and agents on consistent, up-to-date data.