Systems | Development | Analytics | API | Testing

November 2023

Top 4 Challenges to Scaling Snowflake for AI

Organizations are transforming their industries through the power of data analytics and AI. A recent McKinsey survey finds that 75% expect generative AI (GenAI) to “cause significant or disruptive change in the nature of their industry’s competition in the next three years.” AI enables businesses to launch innovative new products, gain insights into their business, and boost profitability through technologies that help them outperform competitors.

Announcing Unravel for Snowflake: Faster Time to Business Value in the Data Cloud

Snowflake’s data cloud has expanded to become a top choice among organizations looking to leverage data and AI—including large language models (LLMs) and other types of generative AI—to deliver innovative new products to end users and customers. However, the democratization of AI often leads to inefficient usage that results in a cost explosion and decreases the business value of Snowflake. The inefficient usage of Snowflake can occur at various levels.

Transforming analytics on the cloud: Supercharge your data applications

Transforming analytics on the cloud: Supercharge your data applications with Databricks, AWS and Unravel Organizations are feeling pressure to launch new data applications faster to meet end-user demand. Cloud data platforms help accelerate launch times with on-demand delivery of infrastructure and pay-as-you-go pricing. Last year, 98% of the overall database management system (DBMS) market growth came from cloud database platform as a service (dbPaaS). 80% of organizations have adopted agile practices to increase their pace of innovation.