SAS' Bahar Biller guides you through an asset lifetime prediction scenario using a synthetically generated historical data set and a solution built on SAS reliability modeling.
Synthetic data generation has intrigued across industries for its many use cases, including fraud detection, clinical trials, worker safety and law enforcement. One of the main benefits is the low cost of creating synthetic data, which is often cheaper than collecting actual demographic, psychographic or behavior-based information. With such data,
Step into the vibrant, insightful platform that is theCUBE, where industry leaders don’t just talk tech; they unpack AI’s impact on our world. Eight quotes aren’t enough to describe all the knowledge shared by SAS leaders during theCUBE’s session at SAS Innovate 2024. But this blog post would go on
