Data cloud World Tour

During this session, we will showcase the challenges faced by our customers and share their success stories on their journey to the cloud.

The discovery of large language models (LLMs) is enabling an array of dazzling new AI apps that can converse and reason remarkably like humans. This talk will explore how Snowflake can help you leverage LLMs for your own data, both now and in the future. You will learn how to build your own LLM-powered app using Snowflake and Streamlit, with live demonstrations of how to use generative AI and LLMs to power natural language data explanation, exploration, recommendation, discussion, and question answering. This talk will also discuss Snowflake’s strategy, including its recent acquisitions of Streamlit and Applica, and present some new AI products being developed in-house. Finally, the speakers will explore this technology’s implications for app development, data storage, processing, and analytics, and conclude with thoughts on how Snowflake can help you navigate this rapidly changing future.

With the Snowflake Native App Framework you can bring your application to your customer’s data, natively in the Data Cloud! Join us to learn from Snowflake product experts and industry-leading customers about how you can use the Snowflake Native App Framework to build Snowflake Native Apps, distribute and monetize them via Snowflake Marketplace, and deploy them directly in your customers’ Snowflake accounts.

Join us to hear the latest enhancements with Apache Iceberg, powering flexibility and open standards in the Data Cloud.

Join us to learn more about the latest enhancements to Snowflake’s integration with Streamlit and how you can start quickly building apps using Python.

Learn how to load data into Snowflake faster. This will be a tour of the speed and efficiency of different ingest patterns and technologies. In this session, you’ll learn best practices and patterns for Snowpipe, Snowpipe Streaming, COPY from external and internal stages, and the Kafka Connector.

Successful adoption of AI/ML are increasingly essential for competitive success: How do you discover, collect, curate, and access the best data sets for optimal business outcomes in AI/ML? How do you avoid fractured data stacks and governance to accelerate successful AI deployments? How do you easily scale your data stack to the demands of AI/ML? And how do you enable seamless collaboration and maximize productivity between ML practitioners and end users-within your own organization and beyond? Enter the Snowflake Data Cloud! In this executive-level session, we will delve into industry trends and challenges, and explore how the Snowflake Data Cloud can accelerate and scale your AI/ML adoption. Hear our perspective, current capabilities, roadmap, and vision for AI/ML. Join us to see how the Snowflake Data Cloud can drive success for you in this exciting field.

With Snowpark Python now generally available, many customers are now able to bring production workloads in Python to Snowflake. But, how? For instance, how should you think about the DataFrame API vs. user-defined functions vs. UDTFs? In this session, you’ll learn core design principles for building capabilities on top of Snowpark Python (across data engineering, data science, and data application workloads).

As organizations scale Snowflake usage to more workloads and use cases, managing and optimizing costs relative to value are critical to success. In this session, Snowflake product management will share our approach to managing costs at Snowflake across the three pillars of visibility, control, and optimization. You’ll see and learn how to use the latest cost optimization features in Snowflake.