TL;DR:
- Snowflake enhances Python capabilities through Snowpark for streamlined ML and app development in the Data Cloud.
- New Snowflake Notebooks provide an interactive environment for Python and SQL users.
- Snowflake introduces ML Modeling API and Operations Enhancements for model development and management.
- The Native App Framework offers building blocks for app development within Snowflake.
- Automation features like Database Change Management simplify DevOps tasks.
- Snowflake’s innovations aim to revolutionize the Data Cloud market.
Main AI News:
In a dynamic showcase at Snowday 2023, Snowflake, the preeminent Data Cloud company, unveiled groundbreaking enhancements that revolutionize the landscape for developers building machine learning (ML) models and full-stack applications within the Data Cloud. Leveraging Snowpark, Snowflake is supercharging its Python capabilities to facilitate higher productivity, foster collaboration, and expedite end-to-end AI and ML workflows. Furthermore, by embracing containerized workloads and expanding DevOps capabilities, developers can now expedite application development and execution, all under the secure and fully managed umbrella of Snowflake’s infrastructure.
“The ascent of generative AI has rendered organizations’ most prized asset, their data, even more invaluable. Snowflake is simplifying the journey for developers to harness that data’s potential, enabling them to craft potent end-to-end machine learning models and full-stack applications natively within the Data Cloud,” expressed Prasanna Krishnan, Senior Director of Product Management at Snowflake. “With Snowflake Marketplace leading the way as the pioneering cross-cloud marketplace for data and applications in the industry, customers can efficiently and securely transition their creations to a global user base, unlocking augmented monetization, discoverability, and utilization.”
Developers Empowered with Robust Functionality for End-to-End Machine Learning
Snowflake’s commitment to Snowpark remains unwavering, with more than 35% of Snowflake customers embracing Snowpark on a weekly basis (as of September 2023). Developers are increasingly turning to Snowpark for intricate ML model development and deployment, and Snowflake is introducing expanded functionality that enhances the accessibility and potency of Snowpark for all Python developers. These innovative strides encompass:
- Snowflake Notebooks (private preview): Introducing Snowflake Notebooks, a novel development interface that provides an interactive, cell-based programming environment for Python and SQL enthusiasts to explore, manipulate, and experiment with data within Snowpark. Snowflake’s integrated notebooks empower developers to author and execute code, train and deploy models using Snowpark ML, visualize results through Streamlit chart elements, and much more — all within Snowflake’s unified, secure ecosystem.
- Snowpark ML Modeling API (general availability soon): Snowflake’s Snowpark ML Modeling API empowers developers and data scientists to amplify feature engineering and streamline model training for swifter and more intuitive model development within Snowflake. Users can natively implement leading AI and ML frameworks on data residing in Snowflake, eliminating the need to create stored procedures.
- Snowpark ML Operations Enhancements: The Snowpark Model Registry (public preview soon) further extends the capabilities of Snowflake, anchoring it as a native Snowflake model entity. It enables scalable, secure model deployment and management within Snowflake, encompassing robust support for deep learning models and open source large language models (LLMs) from Hugging Face. Snowflake also equips developers with an integrated Snowflake Feature Store (private preview) that facilitates the creation, storage, administration, and provisioning of ML features for model training and inference.
Global entertainment conglomerate, Endeavor, which includes WME Agency, IMG & On Location, UFC, and more, relies on Snowflake’s Snowpark Python capabilities to construct and deploy ML models that craft highly personalized experiences and applications to engage fans.
“Snowpark drives our end-to-end machine learning development, enabling us to centralize and process data across our diverse entities securely. It facilitates the construction and training of models using that data, creating hyper-personalized fan experiences at scale,” stated Saad Zaheer, VP of Data Science and Engineering at Endeavor. “With Snowflake serving as our central data foundation, we can unlock even more predictive capabilities to fuel our targeted sales and marketing endeavors.“
Snowflake Elevates Developer Capabilities Throughout the App Lifecycle
The forthcoming Snowflake Native App Framework (soon to be generally available on AWS and in public preview on Azure) equips every organization with the essential building blocks for application development, encompassing distribution, operation, and monetization within Snowflake’s ecosystem. Leading organizations are capitalizing on Snowflake Native Apps through Snowflake Marketplace, with app listings witnessing more than a twofold increase since Snowflake Summit 2023. This number continues to soar as Snowflake diligently augments developer capabilities throughout the application lifecycle, enabling more organizations to unlock substantial business impact.
For instance, Cybersyn, a data-service provider, is exclusively crafting Snowflake Native Apps for Snowflake Marketplace, with over 40 customers executing more than 5,000 queries using its Financial & Economic Essentials Native App since June 2022. Additionally, LiveRamp, a data collaboration platform, has witnessed an over 80% surge in customers deploying its Identity Resolution and Transcoding Snowflake Native App through Snowflake Marketplace since June 2022. Lastly, SNP has empowered its customers with a remarkable 10x cost reduction in Snowflake data processing associated with SAP data ingestion. This has led to a substantial reduction in data latency while enhancing SAP data availability in Snowflake through SNP’s Data Streaming for SAP – Snowflake Native App.
Snowflake Unleashes Automation for DevOps Across Apps, Data Pipelines, and More
Snowflake is introducing new avenues for developers to automate critical DevOps and observability functions spanning testing, deployment, monitoring, and operation of their applications and data pipelines. This streamlined process expedites the journey from conceptualization to production. Snowflake’s novel Database Change Management features (private preview soon) empower developers to code declaratively and seamlessly template their work for efficient management of Snowflake objects across various environments. These features serve as a singular source of truth for object creation across multiple environments, harnessing the “configuration as code” pattern in DevOps to automatically provision and update Snowflake objects.
Furthermore, Snowflake is introducing a groundbreaking Powered by Snowflake Funding Program, facilitating secure access to the prowess of generative AI using enterprise data. These innovations also aim to obliterate data silos and fortify Snowflake’s leadership in compliance and governance through Snowflake Horizon. All these transformative endeavors were unveiled at Snowday 2023, heralding a new era of innovation within the Data Cloud.
Conclusion:
Snowflake’s latest advancements in ML, app development, and automation are poised to reshape the Data Cloud market. Developers can expect streamlined workflows and enhanced collaboration, while organizations can tap into the potential of generative AI, opening up new avenues for monetization and data-driven insights. Snowflake’s commitment to innovation positions it as a key player in the evolving landscape of data and analytics.
