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Key Highlights from Snowflake Summit 2024: AI, Data and Observability

Key Highlights from Snowflake Summit 2024: AI, Data and Observability

June 24, 2024

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The 2024 Snowflake User Conference, 2024 Data Cloud Summit was an excellent conference for data leaders, data engineers, data users and data practitioners. With over 10,000+ data professionals and 100+ companies showcasing their solutions, the event was exceptional for gaining insights into the current state of the data market, customer use cases, investments and hands-on learning.

#1: Snowflake is now a Data, AI and Application Platform

Snowflake has been known for its cloud data platform that offers data warehousing, data lakes, and data sharing designed to handle large volumes of data and complex queries, providing high performance, scalability, and concurrency. With the recent announcements, Snowflake is clearly an AI, Data, and Application platform.  See more below.

This year’s Snowflake Summit was marked by a significant shift, with Snowflake rebranding itself as Snowflake AI Data Cloud.

#2: Key Snowflake Summit Announcements

The list of AI, Data, Applications and Partner related announcements at the Snowflake Summit were many. We have highlighted a few significant ones!

AI and ML Advancements: Snowflake has emerged as an enterprise AI solution provider with advancements to Snowflake Cortex AI and Snowflake ML and new chat experiences for seamless data interaction. To boost developer productivity, Snowflake introduced a no-code AI development platform, Snowflake AI & ML Studio. Additionally, Snowflake is streamlining model and feature management with a unified, governed MLOps solution, Snowflake ML.

Enhancement Developer Capabilities: Snowflake is enhancing developer capabilities by providing end-to-end solutions for building enterprise-grade pipelines, models, and AI-powered applications. The integration of Dynamic Tables and Snowpipe Streaming enables low-latency transformation pipelines within the AI Data Cloud, with over 2,900 customers already utilizing these features. Snowflake Notebooks, now in public preview, offers a unified development interface for Python, SQL, and Markdown, enhancing productivity and collaboration. Additionally, the new Snowpark pandas API allows Python developers to use familiar pandas syntax for advanced AI and pipeline development. Snowflake Trail, a set of observability capabilities, aims to provide visibility and troubleshooting for data quality, pipelines, and applications, integrating with popular observability platforms. The new Snowflake Native App Framework with Snowpark Container Services (public preview on AWS) supports a wide range of applications, further accelerating business growth in the AI Data Cloud.

Solidifying Data Foundation: Snowflake is solidifying its leadership as the premier data foundation for enterprises by enhancing interoperability and governance within the AI Data Cloud. With the general availability of Iceberg Tables, Snowflake allows customers to leverage Apache Iceberg's open table format, enabling seamless access, performance, governance, and collaboration for externally stored Iceberg data. Snowflake is improving its governance solution, Snowflake Horizon, to provide comprehensive compliance, security, privacy, and access capabilities. Additional new capabilities include the Internal Marketplace for securely sharing data products within an organization and Universal Search, which allows users to discover relevant content using natural language across Snowflake storage, external Iceberg storage, and third-party providers.

NVIDIA Collaboration: Snowflake and NVIDIA are empowering customers and partners with customized AI applications through the integration of NVIDIA AI Enterprise software into Snowflake Cortex AI. This collaboration includes key technologies such as the NVIDIA NeMo Retriever for high-accuracy information retrieval and the NVIDIA Triton Inference Server for scalable AI inference across platforms. Additionally, NVIDIA NIM inference microservices, a set of pre-built AI containers, can be deployed within Snowflake using Snowpark Container Services, allowing organizations to easily deploy foundation models. Snowflake Arctic, a state-of-the-art LLM launched in April 2024 and trained on NVIDIA H100 Tensor Core GPUs, is now available as an NVIDIA NIM, providing users with instant access and flexible deployment options via the NVIDIA API catalog.

New Data Catalog and New LLM: Snowflake has introduced the Polaris Catalog with interoperability with major platforms like AWS, Google Cloud, Microsoft Azure, and Salesforce. The Polaris Catalog offers new levels of interoperability for Apache Iceberg, allowing organizations to seamlessly integrate their data operations. Snowflake Arctic, a highly open enterprise-grade large language model, was released with weights under an Apache 2.0 license and detailed training cookbooks. Snowflake now supports the Streamlit open source community, which has grown significantly since Snowflake’s acquisition in March 2022, reaching over 275K monthly active developers and 6 million monthly application views.

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#3: DataOps, Data Observability, FinOps Takes Center Stage

The Revefi team was on-hand at the Snowflake Summit, and we met several hundred Data leaders, technical experts, customers, and business leaders representing a diverse array of backgrounds.

Our conversations were high caliber and they covered a wide spectrum of data-related trends, including GenAI, FinOps, DataOps, Data Observability, Data Quality and  Data Engineering.

Majority of the conversations we had were with Data Engineers, Chiefs Data Officers (CDO) involving Data Observability, FinOps, DataOps and Data Quality. This year, the  discussions were not about not “what" but “how to” optimize data quality, performance, spend, and usage.

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  • 30-50+% reduction in annual Snowflake spend
  • Tens of millions of queries eliminated from warehouses
  • Billions of rows of useless data removed
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