Abstract: Cloud-native data warehouses have revolutionized data analysis by enabling elasticity, high availability and lower costs. And the increasing popularity of artificial intelligence (AI) drives data warehouses to provide predictive analytics besides the existing descriptive analytics. Consequently, more vendors start to support training and inference of AI models in data warehouses, exploiting the benefits of near-data processing for fast model development and deployment. However, most of the existing solutions are limited by a complex syntax or slow data transportation across engines.
Loading