The key to successful artificial intelligence-based advanced analytical training is augmenting internal data with external, according to data science platform startup Explorium Inc.
The process is not easy, though. Problems include getting a hold of and managing that mass of external material.
“The key to any analytical problem is having the right data,” said Zach Booth, director of global partnerships and channels at Explorium.
Models are only as strong as the data they train on, but getting that needed, external data is challenging. “It’s manual, it’s tedious and it’s extremely time consuming,” he said.
Explorium claims it has a solution that includes a curated, data-source catalog coupled with a platform to integrate everything within an organization’s existing, internal material.
Booth spoke with John Furrier, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during the AWS Startup Showcase: The Next Big Things in AI, Security & Life Sciences. They discussed how external data source platforms — taking advantage of the massive amounts of data being generated in the world — could improve and speed up analytical machine learning for individual organizations.