Watch Now

Snowflake AI Data Cloud Day

Modernizing for the AI Era

 

In Partnership with: 
On Demand
Virtual

Now On Demand

Why Attend

The AI era is here, and it demands a flexible and evolving data architecture built for agility, scale, and intelligence—pushing beyond the capabilities of traditional data warehousing and fragmented lakehouse approaches. Join us for AI Data Cloud Day, featuring exclusive access to the most impactful Snowflake Summit sessions—curated for enterprise data architects and technical decision-makers ready to propel their organizations into the future of AI.

This event will provide a deep dive into the principles and practical strategies for modernizing your data architecture, showcasing how the Snowflake AI Data Cloud delivers a truly unified, easy, trusted, and connected platform. Through expert-led sessions, you will learn to assess your current landscape, design architectures for the future, streamline complex data warehouse and Spark migrations, and build highly efficient data pipelines. You’ll discover how to significantly reduce TCO, optimize performance, and ensure data integrity at every stage. Specifically, you’ll walk away with:

  • Clarity on how a modern data architecture on Snowflake accelerates AI innovation and reduces total cost of ownership.
  • Practical strategies for migrating to an easy, trusted, and connected AI and data platform, with inspiration from those who’ve done it successfully.
  • Tools and capabilities to streamline complex migrations and build robust data pipelines and analytics on Snowflake.

Featured Partners

Agenda at a glance

SESSION TYPE SESSION OVERVIEW
Panel
Executive Fireside Chat

AI is reshaping business expectations from their data platforms, making modernization as much about operational and strategic shifts as it is about technology. In this executive fireside chat, leaders from Microsoft and Snowflake will explore what it means to truly modernize in 2025. The discussion will unpack how the definition of modernization has evolved, with an emphasis on cultural mindset, governance, and architectural flexibility. Learn how Snowflake and Microsoft are partnering to help customers simplify migrations, minimize technical debt, and build scalable AI-native architectures using solutions like SnowConvert AI and Microsoft’s ecosystem of services. This conversation will surface the turning points in data strategy and modernization and the decisions that will define the next decade of enterprise growth.

What's New
Accelerating Data Ecosystem Migrations to Snowflake

Discover what’s new in AI-powered migrations. Learn how to accelerate and automate migrations with SnowConvert AI, featuring data ecosystem migration agents powered by Snowflake Cortex AI. SnowConvert AI is your free, automated solution designed to dramatically reduce the complexities, costs, and timelines associated with data warehouse and BI migrations. It intelligently analyzes your existing code, automates code conversion, data validation, and streamlines the entire migration process. Join us for an overview of the solution, migration best practices, and demos.

Data Engineering & Streaming
Mastering Data Engineering Migration to Snowflake

Join this session to learn how to successfully move data engineering workloads to Snowflake. We will share best practices and review reference architectures that can ensure success while migrating to Snowflake. Topics include: Migrating PySpark code, Migrating Notebooks to stored procedures, Data movement: Iceberg tables/Snowflake native tables, Code, testing, CI/CD approaches, performance and optimization considerations, Data validation considerations and anti-patterns/considerations

Platform Migrations
Legacy to Snowflake: How to Avoid Failing Your Data Warehouse Migration

Migrating a legacy data warehouse to Snowflake should be a predictable task. However, after participating in numerous projects, common failure patterns have emerged. In this session, we’ll explore typical pitfalls when moving to the Snowflake AI Data Cloud and offer recommendations for avoiding them. We’ll cover mistakes at every stage of the process, from technical details to end-user involvement and everything in between — code conversion (using SnowConvert!), data migration, deployment, optimization, testing and project management.

Snowpark Connect
Modernizing Data Engineering Workloads

Snowpark Connect for Apache Spark empowers teams to run existing Spark DataFrame, Spark SQL, and UDF code natively in Snowflake — no data movement or major code changes required. In this session, we’ll explore how Snowpark Connect leverages Spark 3.5’s client-server architecture to reduce complexity and improve performance across Spark workloads. Learn how this approach helps organizations modernize their data platforms and lower operational overhead. We’ll also walk through an exciting live demo showcasing real-world data engineering use cases across Snowflake and Iceberg tables.

Platform Migrations
How Snowflake Enables Petabyte-Scale Data Migration, with Real-World Examples

This session will explore strategies for migrating large volumes of legacy data to Snowflake as part of a comprehensive migration project using the prebuilt Data Migration and Validation Accelerator (DMVA) tool by Snowflake Professional Services. We will dive into the tool’s capabilities, the validation techniques employed to ensure accurate data migration and real-world customer examples showcasing its use in migrating massive data quantities.

Platform Migrations
Hitting the Right Notes: Guitar Center's Move to Snowflake

Discover Guitar Center’s journey migrating to Snowflake from a mix of on-prem, Databricks, and other data warehouses. This story will focus on three key questions that will resonate with anyone facing or considering a Snowflake migration, offering practical takeaways: How should you approach your migration strategy?,What operating principles drive migration success? What are the best practices for migrating to Snowflake? We’ll also cover general tips, common challenges and how to estimate ROI.

Watch Now