Snowflake Summit 2023: Innovation, AI, and Beyond
Snowflake Summit 2023, held in Las Vegas, Nevada, from June 26 to June 29, gathered an impressive global audience of 12,000 in-person attendees. Throughout the event, multiple compelling themes emerged, showcasing the evolving landscape of data management and analytics, with a focus on generative AI’s impact on enterprise data innovation.
Here are some of the primary themes that stood out at the event, and where I see the biggest opportunities for data professionals.
Empowering data management with a unified platform
A popular topic of conversation at the Summit was Snowflake’s robust single platform that streamlines and simplifies the data management and analytics processes of organizations. This integrated approach eliminates the complexities of juggling multiple data systems and allows seamless storage, processing, and analysis of data, regardless of how structured it may or may not be.
Snowflake’s unified platform breaks down data silos, simplifies architecture, and ensures a secure, governed environment without the need for external data movement or extra tools. With advancements like large language models (LLMs), support for unstructured data, improved external table performance, ML-powered functions, and various other AI/ML features, Snowflake has become a one-stop solution for all AI/ML, data engineering, data science, and reporting needs.
Monitizing innovation with Snowflake Native Apps
The event brought exciting news about Snowflake Native Apps, a game changer for developers. Snowflake Native Apps allows developers to publish and monetize their apps in the Data Cloud, easily reaching thousands of organizations. The platform’s seamless integration enables organizations to buy these apps, fostering a vibrant ecosystem where data-driven solutions can thrive.
Snowflake Native Apps offer an effortless way to create, distribute, and monetize apps within the Data Cloud. As a consultant, I find the platform’s seamless integration and protection of intellectual property invaluable. Building and deploying apps becomes faster and easier through the Snowflake Marketplace. For consumers, accessing apps means reducing procurement and security concerns, as they can instantly install the app in their own Snowflake environment without moving data. I’m already developing my first Snowflake app, which identifies all personally identifiable information (PII) in Snowflake databases.
Optimizing FinOps and embracing DevOps
Addressing the importance of cost optimization in the cloud, Snowflake showcased a range of FinOps capabilities that empower organizations to manage and optimize their cloud data platform expenses. By providing valuable insights into resource consumption and cost allocation, Snowflake helps businesses make data-driven decisions to enhance efficiency and reduce wasteful spending. Furthermore, the direct Git integration announcement enables full DevOps functionality and allows smooth collaboration between development and operations teams.
As a data architect and engineer, I’m excited about the FinOps and DevOps improvements that Snowflake announced at the Summit, including cost optimization budgets, Snowflake Performance Index, and warehouse utilization optimization. Warehouse utilization optimization addresses the critical issue of right-sizing Snowflake warehouses, ensuring optimal query performance and cost efficiency.
With native Git integration, developers can seamlessly collaborate and work on assets within Snowflake, streamlining workflows and enhancing productivity. These enhancements empower me to deliver more cost-effective and performance-driven solutions to my clients, driving their success with Snowflake’s advanced features.
Additional performance features announced at Snowflake Summit include enhanced support for Iceberg tables, offering both Snowflake and client-managed options. Snowflake-managed Iceberg tables deliver nearly identical performance to native Snowflake tables. Moreover, the introduction of dynamic tables enhances materialized views, enabling joins, unions, aggregates, and window functions, expanding data processing capabilities and further optimizing performance.
LLM and generative AI
Generative AI was the biggest talking point of the conference, with Snowflake showcasing their vision for AI via product announcements, partnerships, and technical sessions. Snowflake’s generative AI and LLMs is a game changer, built on three core principles:
- Unlock the potential of LLMs with your data
- Empower your apps with powerful user interfaces (UIs) using Streamlit
- Seamless integration of native LLMs
Many data architects in attendance were thrilled to hear about these cutting-edge AI/ML features in Snowflake, including:
- ML-powered functions simplify ML frameworks for Forecasting, Anomaly Detection, and Contribution Explorer, empowering analysts with faster and higher-quality decisions through SQL statements.
- Native LLMs integrated into Snowflake boost productivity and reveal invaluable insights from customer data, with Document AI as a prime example. Document AI allows you to query and retrain data within unstructured documents like PDF files.
- Snowpark Container Services allows seamless deployment of containerized data apps with secure Snowflake-managed infrastructure and customizable hardware options, including NVIDIA advanced GPUs and leading LLMs from the Snowflake Marketplace.
- Snowpark ML Modeling API simplifies feature engineering and training with popular ML frameworks directly in Snowflake, improving performance and scalability without the need for manual stored procedures and user-defined functions (UDFs).
- The Snowpark Model Registry empowers organizations to streamline their ML workflows and efficiently manage model deployment, enhancing collaboration and driving better data-driven outcomes for clients.
- Snowpark Copilot is a comment to SQL feature that allows you to write a query in a natural language like “show me the sales by region for the last 30 days.” Snowflake will translate this to SQL and provide the results.
Snowflake and NVIDIA
The most exciting announcement throughout the event was the partnership between Snowflake and NVIDIA. Snowflake and NVIDIA aim to accelerate data analytics and AI capabilities. The partnership involves leveraging NVIDIA’s powerful graphics processing units (GPUs) and their AI libraries to enhance Snowflake’s data processing capabilities.
This partnership is welcome news for consultants. It directly brings the power of NVIDIA’s GPUs and AI libraries into Snowflake’s Data Cloud, boosting data processing and analytics performance. With this collaboration, clients can expect faster insights and improved AI-driven capabilities, empowering them to make better data-driven decisions and stay ahead in the competitive landscape.
Snowflake Summit provided invaluable insights into the future of enterprise data innovation. The event highlighted the transformative potential of generative AI, paving the way for advanced data analysis and decision-making. Snowflake’s unified platform stood out as a game changer, streamlining data management and analytics processes, while Snowflake Apps present an opportunity to monetize innovative solutions within the Data Cloud.
The FinOps and DevOps enhancements showcased at the Summit demonstrated Snowflake’s commitment to optimizing cost efficiency and collaboration in the cloud environment. Overall, the event reinforced Snowflake’s position as a leading force in the data management and analytics landscape, promising more opportunities for data-driven success in the ever-evolving digital age.
Slalom is a global consulting firm that helps people and organizations dream bigger, move faster, and build better tomorrows for all. Learn more about our partnership with Snowflake here.
