Data interoperability is quickly becoming a practical requirement for companies trying to move artificial intelligence into production.
Picking the right model or adding computing capacity is only part of the job. Companies also need reliable data that carries the right business meaning and remains protected as it moves between systems. Snowflake Inc. is building its Amazon Web Services integration around that need. The goal is to give businesses a governed data layer that supports AI and other enterprise workloads without forcing them to create more copies of their information. That approach is changing how companies think about the data beneath their AI systems, according to Zahir Gadiwan (pictured), partner solution engineering leader at Snowflake.
“When customers talk about enterprise AI, the real challenge usually is not finding another model,” Gadiwan said. “The challenge is getting trusted data, business context, governance and scalable infrastructure to work together in one operating model.”
Gadiwan spoke with theCUBE’s John Furrier during an interview for the AWS Marketplace Series on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Snowflake and Amazon Web Services Inc. are helping companies connect governed data while limiting unnecessary movement between platforms. (* Disclosure below.)
