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In regulated, high-stakes markets, data only becomes a business advantage when it’s trusted, consistent, and reusable across products, teams, and customers. In this panel, Nasdaq shares how it’s building a unified intelligence layer—powered by a lakehouse foundation with Databricks and a governed transformation and semantics layer with dbt—to scale analytics across its FinTech portfolio and enable the next wave of AI and agentic workflows.

We’ll cover the operating model behind the shift from bespoke, engineering-heavy ETL to a standards-based, collaborative approach that strengthens governance, auditability, and change control—plus what it takes to keep definitions and “data contracts” stable as upstream systems evolve. Finally, we’ll connect the architecture to outcomes: faster time-to-insight, safer self-service, and a foundation for monetizable data products.