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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Sarah Levy
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Sarah Levy is the Co-founder & CEO of Euno, a metadata management platform built for BI and AI success. With over 25 years of experience, Sarah has driven teams and startups in cybersecurity, healthcare, and finance to extraordinary growth by leveraging data and AI in transformative ways. Her expertise in navigating the complexities of data at scale-up companies has positioned her as a leader in balancing robust data governance with the freedom of analytics. Together with her Euno-tastic team, Sarah’s mission is clear: to untangle the toughest knots for data teams, no matter how fast your company scales.
Bio from: Dbt Coalesce 2024
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