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On Demand | The Modern Data Lifecycle: From Design to Deployment in an AI-Driven World

modern data lifecycle

Modern data platforms are evolving faster than most architectures can support.

Organizations are being asked to enable AI, real-time analytics, and rapidly changing business requirements — while maintaining governance, documentation, and architectural consistency.

The challenge is that most data environments were not designed for this level of change.

In this on demand joint panel with WhereScape and ER/Studio, product leaders and enterprise practitioners will explore what a modern data lifecycle looks like in practice — from establishing a semantic backbone through to automated development, deployment, and ongoing evolution.

What You’ll Learn

  • Why traditional data development lifecycles struggle in modern environments
  • The role of a semantic backbone in supporting architecture, governance, analytics, and AI
  • How data modeling connects design, engineering, and governance
  • What data product–driven delivery looks like in practice
  • Strategies for modernizing existing platforms without disrupting production
  • How to design architectures that adapt to change rather than require rebuilds

Speakers

Moderator

  • Eric Snyder – GM, WhereScape | Former GM, ER/Studio

Panelists

  • Simon Spring – Head of Product, WhereScape
  • Jamie Knowles – Head of Product, ER/Studio
  • Mark Kramm – Founder & Senior Enterprise Data Architect, Enterprise KnowledgePrints
  • Kevin Marshbank – CEO & Principal Consultant, The Data Vault Shop

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