What is the impact of machine learning on dynamic ETL process adaptation based on data patterns?
- Improved adaptability through continuous learning
- Increased processing time for data patterns
- No impact on ETL process adaptation
- Reduced adaptability due to predefined rules
Machine learning positively impacts dynamic ETL process adaptation by continuously learning from data patterns. This enhances the system's ability to adapt and optimize based on evolving data structures and requirements.
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