Practicing analytics well takes more than just tools and tech. It requires data modeling practices that unify and empower all teams within analytics, from engineers to analysts. This is especially true as AI becomes a part of analytics. Without a governed data model that provides consistent data interpretation, AI tools are left to guess. Join panelists Joe Reis, Sarah Levy, Harry Gollop, Rob Hulme, Shachar Meir, and Guy Fighel, as they share battle-tested advice on overcoming conflicting definitions and accurately mapping business intent to data, reports and dashboards at scale. This panel is for data & analytics engineers seeking a clear framework to capture business logic across layers, and for data leaders focused on building a reliable foundation for Gen AI.
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Speaker
Rob Hulme
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Rob Hulme is a seasoned Analytics professional with nearly two decades of experience across e-commerce, healthcare, tourism, and technology sectors. He specializes in building and leading high-performing data teams that drive business innovation and growth. Rob's expertise lies in navigating the complex people and process challenges that arise as organizations rapidly evolve and seek to optimize their data utilization. He excels at implementing strategic solutions that align teams, processes, and technology to unlock the full potential of data-driven decision-making. With a leadership style focused on talent development and fostering collaboration, his approach effectively bridges the gap between data capabilities and organizational objectives, making him a valuable asset in today's business landscape.
Bio from: Big Data LDN 2025
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