Data Management Briefing

AI's potential is hindered by poor data quality. This briefing reveals how data engineering—architecture, infrastructure and security—can transform fragmented data into a robust foundation for impactful AI models. Learn practical strategies to evaluate, build, and deploy data readiness, avoiding common pitfalls and achieving real business outcomes.

Details

Briefing Agenda

AI is only as good as the data it's fed. Too often, organizations struggle to scale AI initiatives not because of weak models—but because their data isn't ready. In this briefing, we cut through the hype and get practical about what's holding AI back: fragmented, poor-quality, and slow-moving data.

You'll learn why data engineering is the most overlooked yet critical factor in AI success. Using real-world examples and engaging storytelling, we'll explore the common pitfalls—like data silos, lack of lineage, and lagging pipelines—that sabotage AI outcomes. We'll then share a practical framework to evaluate, build, and deploy a strong data foundation that fuels accurate, impactful AI models.

What You'll Walk Away With:

Clarity on why your AI may be underperforming (hint: it's not the algorithm).
A breakdown of the three pillars of data engineering: Architecture, Infrastructure, and Security.
A practical, phased approach to improving your data readiness—Evaluate, Construct, Deploy.
Review compelling case-studies and the impact they had on organizations
A better understanding of how to avoid the "AI fails silently" trap.

Why Attend?

If you're investing in AI, this session will help you avoid costly missteps. It's designed for organizations that want to move from frustration to results, with a roadmap that connects data readiness to real business outcomes. The smartest AI in the world can't fix broken data. But the right data engineering can.

Duration: 45–60 minutes

What is a Briefing?

A scheduled event with a WWT Subject Matter Expert — typically via a live Webex — where our expert presents an overview of specific topics, technologies, capabilities or market trends. Your attendees are allotted time for Q&A to pose questions specific to your organization.

Who should attend?

Business and IT leaders exploring or struggling with data preparation for AI initiatives.
CDOs, data owners, line of business owners, and IT Directors. Plus, anyone interested in learning more about how data management approaches can change how they do business today and deliver relevant services to end-users.

Post-Briefing actions?

If the information in this briefing seems too high level or a briefing has already been completed, we offer more in-depth options available for each area of focus.