Modernizing the Data Layer: Designing a Loosely Integrated Architecture for Growth

Description: As communication ecosystems evolve, the ability to introduce new digital services, analytics, and delivery models increasingly depends on the quality of the underlying data layer. Many legacy environments rely on tightly coupled systems and shared databases, making change difficult, slow, and risky.

This session, presented by Jeff DeVoyd, explores how loosely integrated data architectures reduce dependency between systems while improving flexibility and speed. We will review the historical evolution of enterprise data integration, examine the differences between batch and request-driven data exchanges, and discuss how clearly defined data interfaces enable modernization without disrupting core platforms.

Attendees will gain a practical understanding of how to modernize the data layer to support digital expansion, AI readiness, archival requirements, and future service innovation, without breaking what already works.

Key Takeaways:

• • Understand how tightly connected legacy systems limit flexibility and increase risk
  • Apply the core principles of loosely integrated data architecture
  • Differentiate between batch and real-time data exchange models
  • Identify practical steps to modernize your data layer without disrupting core systems