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
Harry Gollop
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Harry Gollop is the Co-Founder of Cognify Search, a data recruitment consultancy specializing in the modern data stack, machine learning, and AI. With a passion for connecting exceptional data talent with forward-thinking businesses, Harry is dedicated to building high-performing teams that drive meaningful impact. As a recognized thought leader in the data space, Harry hosts The Stacked Data Podcast, where he explores modern data challenges with industry experts. He also organises The London Analytics Engineering Meetup, one of the UK’s most vibrant data communities. A strong advocate for diversity and inclusion in data leadership, Harry founded Stacked Pathways, a mentorship program empowering women in data and analytics by connecting them with senior professionals and emerging leaders.
Bio from: Big Data LDN 2025
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