Data Modernization That Holds Under Pressure

Space is limited, so register now for this informative webinar! The webinar will be streamed on Zoom and our YouTube channel and the recording wil be available on YouTube within 24 hours from the webinar’s completion.

Webinar Status

Upcoming

Date & Time

09/02/2026 12:00 pm

Time Zone

Eastern US Time

What You'll Learn

Data Modernization That Holds Under Pressure” makes one central argument: most modernization programs fail not during migration, but during escalation. Platforms get replaced, data gets migrated, pipelines get rebuilt, and leaders declare victory. Then pressure arrives, a number gets challenged, an auditor asks for lineage, an AI initiative scales, and the same structural problems resurface in a more expensive environment.

The briefing reframes modernization as an operating model transformation rather than a technology replacement program. It introduces three pillars that determine whether modernization holds: Architectural Integrity (redesigned, not migrated), Embedded Governance and Data Quality (structural, not symbolic), and Scalable Accountability and Modern Capability (decision rights that scale with technology).

It then walks executives through a five-step maturity path (identify structural debt, define target architecture, embed governance and quality, make accountability explicit, modernize by decision-critical domains) and closes with a 30-second executive diagnostic that scores each pillar Green, Yellow, or Red. The throughline: modern platforms amplify whatever foundation already exists. Upgrade changes technology. Reengineering changes outcomes.

About The Speaker

David Marco PHD EWSolutions

David Marco, PhD

President, EWSolutions

David Marco, PhD is President of EWSolutions and Executive Managing Director of the Global Data Practice. He advises CDOs, CIOs, and executive leadership teams on AI and data governance, decision accountability, and trust in complex, high-stakes environments. David works with organizations to design governance systems that hold under real operational pressure and enable AI outcomes executives can trust.

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