How can AI-driven algorithms enhance data quality checks in ETL testing?
- By automating data quality checks and identifying anomalies
- By eliminating the need for data quality checks
- By focusing solely on quantitative data
- By manual inspection of each data point
AI-driven algorithms enhance data quality checks by automating the process, identifying anomalies, and ensuring consistency in data quality. Automation improves efficiency and accuracy in identifying issues.
Loading...
Related Quiz
- What is a key difference between ETL and ELT processes?
- The use of ________ in data extraction helps in handling semi-structured data.
- What is the primary role of BI tools in the context of data integration?
- ETL testing methodologies will need to adapt to the increasing use of ________ in data management and processing.
- In real-time data integration, testing for ________ is crucial to ensure timely data updates.