Snowflake’s journey in the data space began in 2014 as a cloud-based data warehouse provider, to have now evolved into a multi-cloud data platform that aims to streamline how businesses manage, store, and process data. Speaking with AIM, Murad Wagh, the director of sales engineering at Snowflake, said that at the core of the company’s strategy are the three pillars—data foundation, AI/ML, and data applications.
“We started with a core data foundation that solved the infrastructure management problem that enterprises faced with on-prem solutions like Teradata and Hadoop. By offering a cloud-native, multi-cloud data platform, Snowflake allowed businesses to focus on data outcomes rather than infrastructure challenges,” explained Wagh.
Over time, Snowflake introduced features like data collaboration, enabling companies to securely share data across organisations without having to extract it from the platform. This paved the way for AI and machine learning use cases.
Wagh emphasised that Snowflake’s evolution was driven by …