Snowflake Expands Programmability to Bolster Support for AI/ML and Streaming Pipeline Development

At Snowflake, we’re helping data scientists, data engineers, and application developers build faster and more efficiently in the Data Cloud. That’s why at our annual user conference, Snowflake Summit 2023, we unveiled new features that further extend data programmability in Snowflake for their language of choice, without having to compromise on governance.

Bring Gen AI & LLMs to Your Data

The potential of generative AI and large language models (LLMs) for enterprises is massive. We’ve talked about this opportunity before and at Summit 2023, we announced a number of capabilities that come together to help our customers bring generative AI and LLMs directly to their proprietary data, all delivered through a single, secure platform.

MLOps for Gen AI - MLOPs Live #23 - QuantumBlack AI by McKinsey

In this session, Yaron Haviv, CTO Iguazio was joined by Nayur Khan, Partner, QuantumBlack, AI by @McKinsey and Mara Pometti​, Associate Design Director, McKinsey & Company to discuss how enterprises can adopt GenAI now in live business applications. There was a very engaging Q&A session with many relatable questions asked.

Snowflake Native App Framework

The Snowflake Native Apps Framework revolutionizes the way apps are developed, distributed, and monetized. To illustrate its capabilities, we developed a Snowflake Native App utilizing the preferred tools of developers, and Snowflake first-class functionalities including Streamlit, Snowpark, and Telemetry. We then seamlessly distributed and monetized the app through the Snowflake Marketplace. Last, we demonstrated how consumers can discover, try, purchase and deploy the Snowflake Native App within their accounts, retaining full control of their data.

3 data quality obstacles to beat with Talend and Snowflake

In today's fast-paced, data-driven world, deeper data insights and faster time to value are paramount if you want your business to stay competitive and thrive. Decision-makers need instant access to all their data sources to make sound business decisions — and they need to have trust in their data. However, data quality is often overlooked. According to Gartner, poor data quality costs organizations an average of $12.9 million annually. What’s going on?