AI is moving from experimentation to enterprise-scale execution—and the platform matters. Discover Snowflake CoCo—the intelligent agent built natively into Snowflake that understands your data context, automates end-to-end workflows from ML pipelines to dbt projects, and delivers production-ready code with enterprise security baked in.

In Getting Started with Snowflake CoCo for Data Engineers, a Snowflake expert will demonstrate how to build an end-to-end data engineering pipeline using CoCo — Snowflake’s state-of-the-art AI coding agent.

In Getting Started with Snowflake CoCo for Developers, a Snowflake expert will showcase how developers can leverage CoCo — Snowflake’s advanced AI coding agent — to build faster, smarter, and more efficiently directly within the Snowflake platform.

In Getting Started with Snowflake CoCo for Data Scientists, a Snowflake expert will demonstrate how to harness CoCo — Snowflake’s advanced AI coding agent — to accelerate experimentation, model development, and analytics workflows directly within Snowflake.

This Virtual Hands-On Lab is designed for those new to Snowflake CoCo. Tailored for roles ranging from IT Managers and Data Architects to Developers, this session will help build your skills and confidence in the AI Data Cloud.

Modernising a legacy data estate is complex — from embedded procedural logic to large-scale data movement and tight timelines. In this session, discover what’s new in helping organisations accelerate modernisation on Snowflake. We’ll showcase the latest innovations that reduce risk, disruption, and manual effort through automation, AI-assisted remediation, workload analysis, and database virtualisation. Learn how teams migrate with greater flexibility, minimize code rewrites, validate with confidence, and transition to a scalable, cloud-native foundation for analytics and AI.

Interested in learning how you can track and analyze your Snowflake spend and control your overall spend? If you are, this session is for you. Come learn about Snowflake’s new cost governance capabilities and how customers are leveraging them to manage Snowflake costs effectively.

Learn how the SAP and Snowflake partnership is fueling advanced analytics and AI/ML on a unified enterprise data foundation—bringing together SAP and non-SAP data in the Snowflake AI Data Cloud with zero-copy, preserving governance, interoperability and semantics. See how SAP Business Data Cloud (BDC) data products can be enriched with enterprise and third-party data in Snowflake to unlock intelligent analytics and enterprise AI at scale.

Traditional integrations require costly data replication and create operational lag. In this session, we will demonstrate how Snowflake Zero-Copy, Bidirectional Integration can archive near real-time connectivity between Snowflake and enterprise applications without data movement. We will showcase implementations with Salesforce, Workday and more to explore how we maintain data consistency across systems.

In this interactive lab, participants will diagnose real-world performance bottlenecks and apply optimisation techniques to reduce cost and improve query efficiency. Explore clustering strategies, warehouse right-sizing and query profile analysis in a guided, practical environment.

Stop struggling with fragmented logic and start building a Trusted data foundation in minutes. Join us to see how Easy it is to create Snowflake Semantic Views that turn raw data into governed, actionable insights. We’ll demonstrate how our Connected ecosystem allows your business logic to flow seamlessly from your data cloud to your AI agents and BI tools. Featuring a live demo of our latest “Easy-to-Build” semantic innovations

Make your data AI-ready with the powerful combination of dbt Projects and Snowflake Semantic Views. This session demonstrates how to leverage both SQL and Python DataFrame models in dbt for flexible data engineering that appeals to Spark developers and SQL practitioners alike. Explore semantic layers, the Open Semantic Initiative (OSI) and best practices for managing semantic view lifecycles in Snowflake. Watch CoCo’s AI coding agent accelerate dbt Project development in real time, and learn to automate deployments with Snowflake CLI. Walk away with a complete, modern approach to building AI-ready data pipelines that empower both AI models and analytics tools.

Make your data AI-ready by adding semantic context with Horizon Catalog. Enable AI agents to discover, understand, and reason over your governed data assets.

This 90-minute hands-on lab demonstrates how to create a semantic layer in Snowflake using semantic views. Attendees will learn to leverage features such as Semantic View Autopilot and CoCo to accelerate the creation of a governed data model. You will build a single source of truth that can be accessed by traditional BI tools and used in tandem with Snowflake Cortex AI to enable the fast deployment of complex, robust chatbots and AI tools.

AI is only as powerful as the context it understands. In this session, discover what’s new in Snowflake Agentic Enterprise tools, the enterprise intelligence agent built to turn all your knowledge into trusted business decisions. Learn how organizations are moving beyond dashboards to uncover the critical “why,” grounded in governed enterprise data and shared business definitions. Discover how Snowflake’s Agentic Enterprise tools work together to move teams beyond static insights, enabling natural language intelligence, trusted reasoning, and actionable workflows that help organizations analyze, act, and drive outcomes with confidence.

What if you could go from a blank notebook to a monitored production model using just natural language? CoCo brings agentic AI to the Snowflake ML lifecycle by training models, engineering features with Snowflake Feature Store, registering and versioning models in Model Registry, deploying real-time inference endpoints on Snowpark Container Services, running batch predictions at scale with ML jobs, tracking experiments and more. In this session, we demo the full journey: explore data, train a model, build feature pipelines, deploy to a GPU endpoint and set up monitoring — all driven by an AI agent through conversation. See how agentic ML development collapses weeks of MLOps into minutes.

When intelligence meets enterprise-grade orchestration. See how to build a production-ready multi-agent supply chain orchestrator that combines Snowflake Cortex AI’s deep data intelligence with Amazon Bedrock AgentCore’s enterprise-grade security and dynamic scaling to deliver unified analytics through a single conversational interface. By using the Model Context Protocol (MCP) as the open standard connecting both ecosystems, we’ll demonstrate how Snowflake Cortex Agent (with Cortex Analyst for text-to-SQL and Cortex Search for semantic retrieval) integrates with Bedrock AgentCore—which provides the secure, scalable runtime to orchestrate agents in production.

The introduction of the Snowflake-managed MCP server has generated significant customer interest and practical deployment questions. This session directly addresses the most common challenges we’ve observed across numerous customer engagements, specifically focusing on server setup, secure authentication, tool integration and establishing external client connectivity. Attendees will gain practical guidance and validated best practices derived from real-world deployments to ensure a seamless and successful MCP implementation.

Build a complete AI retail app entirely in Snowflake. Start by using CoCo to generate SQL and dbt models for metrics such as CLV. Next, train a GPU-accelerated XGBoost model in Snowflake Notebooks, register it, and deploy it as a service. To handle OLTP, use Snowflake Postgres and sync data to Apache Iceberg on S3, demonstrating lakehouse interoperability with pg_lake. Finally, unify the stack with Snowflake’s agentic enterprise tool, a conversational interface orchestrating Snowflake Cortex Analyst, Snowflake Cortex Search and your ML models for a seamless analytical experience.

AI is moving from experimentation to enterprise-scale execution—and the platform matters.

In this session, discover Snowflake CoCo—the intelligent agent built natively into Snowflake that understands your data context, automates end-to-end workflows from ML pipelines to dbt projects, and delivers production-ready code with enterprise security baked in.

Available now in Snowsight and the CLI, CoCo empowers teams to move from idea to implementation faster than ever—embedding intelligence directly where governed enterprise data lives.
Through compelling demos and real-world scenarios, see how organizations are accelerating development, automating complex workflows, and unlocking new value across the AI Data Cloud.
The future of data development is agentic—and it’s here today.

This Virtual Hands-On Lab is designed for those new to Snowflake CoCo. Tailored for roles ranging from IT Managers and Data Architects to Developers, this session will help build your skills and confidence in the AI Data Cloud.

Building a complete data solution from ingestion to insights takes too long. Currently, data engineers spend hours configuring connectors and stitching together brittle pipelines, while analysts are stuck in a perpetual backlog just to get answers to simple questions. Everyone deserves a faster path from raw source data to conversational insights without wrestling with documentation or boilerplate code.

CoCo changes the math by bringing AI-powered assistance to every stage of your data journey. Available in both Snowsight’s familiar web interface and as a full-featured CLI, it acts as a single AI assistant guiding you through the entire workflow—from deploying connectors to building conversational interfaces.

In this hands-on lab, we’ll move through that entire journey together. We will start by deploying an Openflow SQL Server Connector for seamless ingestion, then use AI to explore and understand the structure of the loaded data. From there, you’ll build dbt models and dynamic tables for transformation and define your business logic via a semantic view. Finally, we’ll bring it all to life by integrating that view into a Cortex Agent.

You’ll walk away not just with a demo, but with the hands-on experience needed to bridge the gap between raw source systems and plain-English business answers. Whether you’re a builder or an architect, you’ll leave with a blueprint for a complete, AI-driven data solution.

This Virtual Hands-On Lab is designed to help you use CoCo Snowsight — the AI coding assistant built into Snowflake’s web interface — to go from raw data to a fully operational analytics pipeline without writing a single line of code manually. Every exercise runs entirely inside Snowsight. No terminal, no extensions, no external tooling.