SEP has been building software products for over 30 years, but data as a dedicated practice is newer. In this episode, Zac Darnell sits down with SEP's Director of Data, Jason LaJeunesse, and Solution Architect Jason Dossett to unpack how SEP thinks about data: what it is, why it matters now more than ever, and what companies get wrong when trying to move fast on AI without the right foundation underneath it.

The conversation moves from definitions (what "data as a product" actually means versus the operational databases most software shops have always built) to the real-world patterns SEP has seen work (and fail) inside energy, aerospace, and other complex organizations.

We dig into how modern data platforms have shifted from a single analyst's concern to a strategic business asset, why the rise of agentic AI has made governance non-negotiable, and what an incremental goal-oriented approach to data strategy actually looks like in practice. The Jasons also make the case that the biggest gap inside most organizations isn't technology. It's enablement.

Takeaways from this episode:

• Data as a service isn't about operational databases powering apps. It's about centralized, strategic platforms with downstream use cases across the business
• Analytics engineering applies software engineering disciplines (version control, DevOps, automated documentation) to data work, and it's a natural fit for SEP's background
• LLMs don't have your business context. Without good data grounding, governance, and role-based access controls, agentic systems can't operate safely
• The "big bang" approach to governance almost always fails. Start goal-oriented, slice vertically, and let governance mature incrementally
• Many organizations are missing an enablement layer, someone who bridges the platform team and the people trying to use it
• Platform engineering is becoming a more critical discipline as AI commoditizes work below the platform level

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