How do you implement agentic AI for automated data warehouse ETL optimization?
ETL optimization agents analyze extract-transform-load pipeline performance and recommend improvements. Configure agents with access to ETL pipeline metrics, query execution plans, and data warehouse performance data. The agent profiles pipeline stages to identify bottlenecks in extraction, transformation, and loading phases. Implement recommendations for parallel execution, incremental loading, and partition-based processing. Optimize transformation logic by identifying redundant calculations and suggesting materialized intermediate results. Analyze data warehouse query patterns to recommend pre-aggregation and denormalization opportunities. Generate optimization reports with specific changes and projected performance improvements. Track pipeline execution time trends and cost per load. Support automated implementation of approved optimizations with rollback capabilities.