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Sami Hero

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Sami Hero is the CEO of Ellie.ai, a category-defining SaaS platform that empowers organizations to design, align, and deliver data products collaboratively. With a career spanning over 30 years, Sami brings a rare dual perspective shaped by leadership roles in both agile startups and large global enterprises.

Before joining Ellie.ai, Sami held senior executive positions across the SaaS landscape from scaling fast-moving startups to driving transformation in multinational corporations. His experience includes leading global teams in North America and Europe across product, marketing, operations, and go-to-market functions. He has successfully navigated hypergrowth, M&A integrations, and global expansion initiatives, always with a sharp focus on customer value and team alignment.

At Ellie.ai, Sami is passionate about bridging the gap between business and IT. Under his leadership, the company is redefining how organizations build trust in data, not just through technology, but by turning data into a shared language that drives decision-making across all domains.

Sami is a frequent speaker and author on data collaboration, domain-driven design, and scaling SaaS businesses. He speaks five languages and is based in Finland.

Bio from: Big Data LDN 2025

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Join Sami Hero and Tammie Coles, as they share how Ellie is reinventing data modeling with AI-native tools that empower both technical and non-technical users. With CData Embedded Cloud, Ellie brings live metadata and data models from systems like Snowflake, Databricks, and Oracle Financials into a unified modeling workspace. Their platform translates legacy structures into human-readable insights, letting users interact with a copilot-style assistant to discover, refine, and maintain data models faster—with less reliance on analysts.

You’ll see how Ellie uses generative AI to recommend new entities, reconcile differences between models and live systems, and continuously document evolving data environments. Learn how corporations are using Ellie and CData together to scale high-quality data modeling across teams. reducing rework, accelerating delivery of analytics-ready models, and making enterprise architecture accessible to the business.