Topic

The Evolution of Data Development Processes in the Age of Big Models

Traditional data integration, development, and ETL processes are both labor-intensive to debug and optimize, and prone to sensitive data leakage; optimization of tasks also has a high threshold, and can usually only be carried out by experienced experts. With the increasing capability of AI big models, a lot of knowledge and experience can be grasped by AI, and combined with unified intelligent metadata management, development efficiency can be greatly improved, including automated task authoring, performance optimization, problem discovery and so on. This sharing will introduce how to optimize the data development process with AI.