Today, we’re excited to announce the general availability of the Snowflake Native App Framework on AWS and Azure! We’ve seen incredible momentum around Snowflake Native Apps. More than 90 Snowflake Native Apps are currently available in Snowflake Marketplace. You can purchase, install and run Snowflake Native Apps—ranging from connectors to clean rooms—directly in your Snowflake account.

In the buildup to this week’s World Economic Forum Annual Meeting in Davos, Switzerland, the talk of polycrisis becoming permacrisis painted a picture of impending doom. These terms have been used to describe the global condition today, citing the “cascading and connected crises” triggered by war and geopolitics, economic uncertainty, and environmental concerns, and their persistence.

Imagine seamlessly integrating your Google Analytics data with Snowflake, allowing you to combine it effortlessly with other key sources like CRM, ERP, social media metrics, email campaign data, and whatever data sources compose the full scope of your data estate. The good news is that it’s possible with the native Snowflake Connector for Google Analytics, now available in public preview.

A key benefit of the Snowflake Data Cloud is the elimination of data silos. Fundamental to this outcome is the ability of customers to operate and collaborate globally. To support this, the Data Cloud was designed to provide customers with the same product experience—including security and governance capabilities — across multiple cloud regions with the three major cloud providers: AWS, Azure, and Google Cloud.

This year may be the most innovative on record. Recent advances in AI are beginning to transform how we live and work. And the potential impacts of artificial intelligence (AI) on the healthcare and life sciences industries are expected to be far-reaching. It’s essential for organizations to leverage vast amounts of structured and unstructured data for effective generative AI (gen AI) solutions that deliver a clear return on investment.

Governments collect more data than any other type of entity on the planet, yet their ability to use data to serve citizens more effectively has always been limited. Regulatory compliance, budgetary constraints, reliance on legacy systems and internal resistance to change all play a role. That’s why when it comes to adopting new technologies, public agencies tend to lag behind the private sector by 18 to 24 months—and often longer.

Many developers and enterprises looking to use machine learning (ML) to generate insights from data get bogged down by operational complexity. We have been making it easier and faster to build and manage ML models with Snowpark ML, the Python library and underlying infrastructure for end-to-end ML workflows in Snowflake.

Advanced analytics help manufacturers extract insights from their data and improve operations and decision-making. But for manufacturers, it’s often challenging to perform analytics with ERP data. Because of the high rate of M&A activity in the industry, manufacturing enterprises often struggle with multiple ERP instances. A fragmented resource planning system causes data silos, making enterprise-wide visibility virtually impossible.

The sheer breadth of data that telecommunications providers collect day-to-day is a huge advantage for the industry. Yet, many providers have been slower to adapt to a data-driven, hyperconnected world even as their services — including streaming, mobile payments and applications such as video conferencing — have driven innovation in nearly every other industry. The speed with which generative AI will change how we work, live, communicate and entertain ourselves is nearly unfathomable.

In the final month of 2023, Snowflake released features around Snowflake Cortex functions, Snowpark ML, cost management and more. Read on to learn more about everything we announced in December.