Joost Visser

Adaptive Data Profiling with ML-Based Quality Checks for ETL Pipeline Quality and Cost Optimization

This thesis investigates whether machine learning can automatically learn what normal data looks like and reliably flag deviations, serving as a low-cost complement to rule-based checks at the point where data first enters the pipeline, and whether AutoML-based anomaly detection is a practical complement to rule-based...