Most organizations don't struggle because they lack data — they struggle because they can't trust it. One dashboard says revenue is up, another says it's down, and teams spend meetings debating numbers instead of making decisions. The September workshop tackles why that happens and how modern data foundations are designed to prevent it, moving from architecture and modelling through to shared definitions and AI-ready design.

In this preview session, we'll cover:

• What the workshop covers — modern data architecture fundamentals, the data gold layer, semantic and self-service design, and data design for AI

• Who gets the most out of it, from data leaders and product managers to engineers, analysts, and anyone responsible for data outcomes

• What participants can expect to take back to their teams

• Your questions, answered live — including anything about format, prerequisites, or fit.

Whether you're already registered or still deciding, this is a low-commitment way to see what's in store before the early bird window closes.

Free to attend this information session. Registration required.

Don't forget to register for the workshop itself at Introduction to building Data Foundations: From Messy Data to Scalable Analytics which is a paid event.

This Semantic Modelling Workshop takes place Thursday, September 18, 2026, 8:30 AM – 3:30 PM at George Brown College, Waterfront Campus. It's a full day of hands-on sessions on modern data architecture, the data gold layer, semantic and self-service design, and designing data for AI — led by Dil Mustafa, Suraj Lamgaday, Miles Garvey, and Kyle Nesbit, with structured networking built into the day. Coffee on arrival and a light lunch are included.

Seats are limited and early bird pricing is only available for a short time, so we'd encourage you to secure your spot and join the session on August 7th if you already know you'd like to attend.

About the Presentor:

Miles Garveyis a modern data strategist with cross-sector experience spanning public institutions, consulting, and high-growth private companies. With a background rooted in analytics engineering and data infrastructure, he has helped organizations evolve from fragmented reporting cultures into insight-driven, self-service ecosystems. Miles brings a holistic understanding of how data works in the real world. He speaks frequently about the evolving role of analytics teams, the future of data ownership, and how organizations can adopt AI-native infrastructure.

Most recently in the private sector, he led analytics and data platform initiatives at G2, where he built scalable data pipelines, implemented semantic layers, and AI-integrated analytics. Currently, Miles runs his own data advisory consultancy spanning larger institutions.