Advanced risk management in ETL testing involves using __________ to predict potential failures.
- Machine learning algorithms
- Predictive analytics
- Regression analysis
- Statistical models
Advanced risk management in ETL testing often involves the use of machine learning algorithms. These algorithms analyze historical data patterns and identify potential failure points, helping testers anticipate and address risks effectively.
Loading...
Related Quiz
- Which ETL testing type is essential to ensure data integrity during the loading phase?
- How does boundary value analysis benefit test case design?
- In BI tool integration, ETL processes are optimized for ________ to ensure data accuracy.
- If discrepancies are found in source-to-target count during ETL testing, what potential issues should be considered?
- In complex Data Warehousing, ________ is used to manage and store high volumes of diverse data.