Virtual Roundtable
AI-Ready Open Data: Building Interoperable Data Architectures with Google Cloud & Snowflake
September 9th, 2026 | 1:00 pm ET / 10:00 am PT
Open data architectures are no longer a technology choice. They are the foundation for scaling AI.
As organizations accelerate their AI strategies, many are still constrained by fragmented data environments, rigid architectures, and costly data movement across clouds and platforms. To operationalize AI at scale, enterprises need open, interoperable data foundations that simplify access, strengthen governance, and enable innovation without vendor lock-in.
This interactive discussion will focus on how Snowflake and Google Cloud enable AI-ready open data architectures through Apache Iceberg open standards, allowing enterprises to securely access, govern, and activate data stored in Snowflake, Google Cloud, and other Iceberg-compatible systems without duplication or movement.
Join IDC, Google Cloud, and Snowflake
for an exclusive executive virtual roundtable exploring how organizations are modernizing their data architectures to support the next generation of analytics and AI workloads.
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By 2028, the worldwide Big Data and Analytics software market exceeds $300B, with AI Software Platforms leading the headline. The data-platform layer underneath it is where open, interoperable architectures are now strategic ground: relational data warehouses, nonrelational analytic data stores, query and reporting tools, and the integration and integrity layer collectively form the foundation every AI workload runs on.
The signal for senior data leaders is clear: the data foundation is consolidating around open table formats and interoperable engines.
Discussion Themes
Four Conversations Every Senior IT Leader Should Be Having Right Now
Break down data silos across clouds
How leading enterprises are using Apache Iceberg and open table formats as the unifying layer across Snowflake, BigQuery, and multi-cloud estates. Why open standards are now the architectural principle that lets data stay in place while engines change.
Accelerate AI and advanced analytics
Trusted, high-quality data is the rate-limiter on production AI, not model choice. How leaders are building AI-ready foundations that serve ML, generative AI, and agentic workloads with consistent, reusable enterprise context.
Reduce complexity and data movement costs
Bringing compute to the data, not the other way around. How federated, multi-engine architectures cut duplication, egress, and pipeline sprawl while accelerating time-to-insight across hybrid and multi-cloud environments.
Extend governance across open data environments
Open does not mean ungoverned. How leaders are extending consistent security, lineage, and policy controls, so the same data is trusted by every engine that touches it.
What To Expect
A live video meeting led by a skilled host/moderator
An intimate gathering of senior leaders from diverse industries, grappling with similar issues
A secure, private conversation open only to a carefully vetted group (no recording, no playback)
Your hosts
Mary Johnston Turner
Research Vice President, Global Lead, Digital and Datacenter Infrastructure and Services
IDC
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Mary Johnston Turner
Mary Johnston Turner is Research VP within IDC’s enterprise infrastructure global research domain. She is the global subdomain lead for Digital and Datacenter Infrastructure and Services. She and her team oversee IDC’s research on datacenter facilities, service provider and owner operators as well as tracking enterprise tech buyer sentiment and strategies related to using digital infrastructure to drive business outcomes. Mary collaborates closely with semiconductor, cloud services, and enterprise infrastructure and services teams produce a comprehensive view of the dynamics, competitive positions and market opportunities created by various IT and non-IT technologies influencing datacenter infrastructure and services.
Ms. Turner is a long-time industry veteran who has worked at a range of analyst and vendor firms. During her career she has covered the evolution of infrastructure, infrastructure software, and infrastructure operations vendors and enterprise priorities. Most recently, she helped lead infrastructure research supporting IDC’s AI Council research series, studied the impact of agentic AI on the transformation of infrastructure operating models, and analyzed enterprise digital infrastructure maturity and tech debt modernization priorities including mainframe infrastructure strategies.
James Rowland-Jones
Director of Product Management
Snowflake
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James Rowland-Jones
Vinod Ramachandran
Product Manager, Engineering GCP BigQuery Core
Google Cloud
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Vinod Ramachandran
Partners
Sponsored By
Google Cloud
Google Cloud accelerates every organization’s ability to transform with Google’s powerful, optimized AI stack.
snowflake
Snowflake delivers the AI Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the AI Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the AI Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the AI Data Cloud.