Seismic shift Large Language Models are unleashing on data engineering, challenging traditional workflows. LLMs obliterate inefficiencies and redefine productivity. AI powerhouses automate complex tasks like documentation, code translation, and data model development with unprecedented speed and precision. Integrating LLMs into tools promises to reduce offshore dependency, fostering agile onshore innovation. Harnessing LLMs' full potential involves challenges, requiring deep dives into domain-specific data and strategic business alignment. Session will addresses deploying LLMs effectively, overcoming data management hurdles, and fostering collaboration between engineers and stakeholders. Join us to explore a future where LLMs redefine possibilities, inviting you to embrace AI-driven innovation and position your organization as a leader in data engineering.

Join us to hear about how National Australia Bank (NAB) successfully completed a significant milestone in its data strategy by decommissioning its 26-year-old Teradata environment and migrating to a new strategic data platform called 'Ada'. This transition marks a pivotal shift from legacy systems to a modern, cloud-based data and AI platform powered by Databricks. The migration process, which spanned two years, involved ingesting 16 data sources, transferring 456 use cases, and collaborating with hundreds of users across 12 business units. This strategic move positions NAB to leverage the full potential of cloud-native data analytics, enabling more agile and data-driven decision-making across the organization. The successful migration to Ada represents a significant step forward in NAB's ongoing efforts to modernize its data infrastructure and capitalize on emerging technologies in the rapidly evolving financial services landscape

The role of data teams and data engineers is evolving. No longer just pipeline builders or dashboard creators, today’s data teams must evolve to drive business strategy, enable automation, and scale with growing demands. Best practices seen in the software engineering world (Agile development, CI/CD, and Infrastructure-as-code) from the DevOps movement are gradually making their way into data engineering. We believe these changes have led to the rise of DataOps and a new wave of best practices that will transform the discipline of data engineering. But how do you transform a reactive team into a proactive force for innovation? We’ll explore the key principles for building a resilient, high-impact data team—from structuring for collaboration, testing, automation, to leveraging modern orchestration tools. Whether you’re leading a team or looking to future-proof your career, you’ll walk away with actionable insights on how to stay ahead in the rapidly changing data landscape.

Atlassian is rebuilding its central lakehouse from the ground up to deliver a more secure, flexible and scalable data environment. In this session, we’ll share how we leverage Unity Catalog for fine-grained governance and supplement it with Immuta for dynamic policy management, enabling row and column level security at scale. By shifting away from broad, monolithic access controls toward a modern, agile solution, we’re empowering teams to securely collaborate on sensitive data without sacrificing performance or usability. Join us for an inside look at our end-to-end policy architecture, from how data owners declare metadata and author policies to the seamless application of access rules across the platform. We’ll also discuss lessons learned on streamlining data governance, ensuring compliance, and improving user adoption. Whether you’re a data architect, engineer or leader, walk away with actionable strategies to simplify and strengthen your own governance and access practices.

Modern insurers require agile, integrated data systems to harness AI. This framework for a global insurer uses Azure Databricks to unify legacy systems into a governed lakehouse medallion architecture (bronze/silver/gold layers), eliminating silos and enabling real-time analytics. The solution employs: Medallion architecture for incremental data quality improvement. Unity Catalog for centralized governance, row/column security, and audit compliance. Azure encryption/confidential computing for data mesh security. Automated ingestion/semantic/DevOps pipelines for scalability. By combining Databricks’ distributed infrastructure with Azure’s security, the insurer achieves regulatory compliance while enabling AI-driven innovation (e.g., underwriting, claims). The framework establishes a future-proof foundation for mergers/acquisitions (M&A) and cross-functional data products, balancing governance with agility.

In today's rapidly evolving digital landscape, organizations must prioritize robust data architectures and AI strategies to remain competitive. In this session, we will explore how Procter & Gamble (P&G) has embarked on a transformative journey to digitize its operations via scalable data, analytics and AI platforms, establishing a strong foundation for data-driven decision-making and the emergence of agentic AI.Join us as we delve into the comprehensive architecture and platform initiatives undertaken at P&G to create scalable and agile data platforms unleashing BI/AI value. We will discuss our approach to implementing data governance and semantics, ensuring data integrity and accessibility across the organization. By leveraging advanced analytics and Business Intelligence (BI) tools, we will illustrate how P&G harnesses data to generate actionable insights at scale, all while maintaining security and speed.

In an era where data drives strategic decision-making, organizations must adapt to the evolving landscape of business analytics. This session will focus on three pivotal themes shaping the future of data management and analytics in 2025. Join our panel of experts, including a Business Analytics Leader, Head of Information Governance, and Data Science Leader, as they explore: - Knowledge-Powered AI: Discover trends in Knowledge-Powered AI and how these initiatives can revolutionize business analytics, with real-world examples of successful implementations. - Information Governance: Explore the role of information governance in ensuring data integrity and compliance. Our experts will discuss strategies for establishing robust frameworks that protect organizational assets. - Real-Time Analytics: Understand the importance of real-time analytics in today’s fast-paced environment. The panel will highlight how organizations can leverage real-time data for agile decision-making.