Susan Laine

Most organizations don't have a data problem — they have a data management gap. The distance between a well-defined data model and a trusted, self-service data product that business teams can actually use is where value goes to die — this session closes that gap. We'll walk through how Quest's portfolio of solutions drives a complete data management journey — from foundational modeling through integration, quality, cataloging, and all the way to publishing data products into an internal marketplace for self-service access inside Databricks. The result: data that arrives in Databricks already understood, already trusted, and ready to drive real business outcomes — with zero-downtime transitions and no disruption along the way. Whether you're an executive accountable for data value, an engineer building and managing pipelines, or a business user tired of waiting on IT to get you what you need — this session will show you a better way to manage data end-to-end.

What if data products could be built in days, not months — and deployed directly into Databricks? We'll introduce the Automated Data Product Factory (ADPF): a model-first framework that transforms how organizations define, govern, and publish data products at scale. We’ll walk through a live use case showing how to automate data product publishing into Databricks and Unity Catalog, using logical specifications to accelerate time-to-value across your data landscape — without rebuilding everything from scratch on each platform. You'll walk away understanding: How the ADPF generates logical data product specs How those specs power automated publishing into Databricks & Unity Catalog What a model-first strategy means for governance at scale Best for: CDOs, CDAOs, and data leaders accountable for AI-ready data; Data Engineers and Architects scaling delivery across hybrid environments; and Business Users ready to create data products tied to real outcomes, without going to IT.

Data leaders must drive bold AI adoption while delivering the guardrails, data context, and quality needed for valuable business outcomes. In this Quest Software blueprint session, hear how Tokio Marine HCC is rapidly scaling its delivery of business effective data products, strengthening data trust and consumability, and using AI as an accelerator.

Building an AI‑ready data foundation is complex in hybrid, multi‑platform estates. In this Quest blueprint session, see how evolving to a modern data architecture with “just enough governance” can help overcome platform‑specific visibility gaps and improve data knowledge, trust and use. Hear a practical approach to developing a context‑rich semantic layer for LLMs and how GenAI can scale data products delivery.