Virtual Roundtable
AI-Ready Open Data: Building Interoperable Data Architectures
October 6th, 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.
Register Now
In 2026, worldwide spending on core Data and Analytics software reaches roughly $167.8B, led by Data Warehouses and Lakehouses at $54.2B.
Business Management and Industry Analytic Applications ($33.6B) and Business Intelligence Software ($27.4B) follow, while newer categories like Decision Intelligence Platforms and Non-Schematic Database Management Systems remain under $3B each.
The signal for senior data leaders: spending is still concentrated in foundational data platforms, with AI-native tooling still scaling up beneath it.
Source: IDC Worldwide Data & Analytics Spending Guide, 2026
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
Marlanna Harrington
Senior Research Analyst, Data Platforms
IDC
Read bio
Marlanna Harrington
Marlanna Harrington is a Research Analyst on the data, analytics, AI, and automation team. Ms. Harrington’s research concentrates on data platforms, including data warehouses, lakes, and lakehouses, focusing on data storage and management. She examines core technologies for implementing analytic data platforms across various environments, data modeling techniques, and emerging open table structures. Her research closely aligns with the data control plane that helps govern and manage data, all in preparation for analytics that provide data-driven solutions to impact business operations.
Marlanna has covered a wide range of research topics during her time at IDC. She started out in consumer research analyzing consumer attitudes, behaviors, technology usage, spending, brand perceptions, etc. When transitioning over to the data and analytics team at IDC, Marlanna focused on data analytic tools and their impact on enterprise decision-making. Her research was centered around business intelligence, geospatial data management and analytics as well as enterprise performance management software.
Parth Desai
Product Manager – Engineering
GCP BigQuery Core
Read bio
Parth Desai
James Rowland-Jones
Director of Product Management
Snowflake
Read bio
James Rowland-Jones
Partners
Sponsored By
Google Cloud
Google Cloud offers a powerful, optimized AI stack—including AI infrastructure, leading models like Gemini, data management capabilities, multicloud security solutions, developer tools and platform, as well as agents and applications—that enables organizations to transform their business for the Agentic Era. Customers in more than 200 countries and territories turn to Google Cloud as their trusted technology partner.
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.