As organizations scale analytics and AI initiatives, data architecture has become mission-critical. Enterprise teams must deliver governed, AI-ready data faster while managing hybrid environments, legacy warehouse complexity, and rising infrastructure costs.
In this recorded DBTA roundtable, industry experts share what is actually working inside modern data environments. The discussion focuses on real-world architectural decisions, deployment lessons, and operational practices that improve reliability, performance, and governance at scale.
The discussion covers:
- Scalable, governed architectures for analytics and AI
- How teams unify data engineering, governance, and AI across hybrid and cloud platforms
- Practical patterns including lakehouse, data products, and semantic layers
- Lessons learned from modernization and migration initiatives
- Best practices for cost efficiency, reliability, and performance
You’ll leave with practical insight into how mature organizations are modernizing data platforms while maintaining control, compliance, and long-term sustainability.
Moderator
Stephen Faig, Research Director, Unisphere Research and DBTA
Speakers
Bassam Chahine, Principal Consultant, NetApp Instaclustr
Paul Watson-Gover, Senior Solutions Architect, WhereScape
Michael Cucchi, Chief Marketing Officer, Hydrolix
