A company faces challenges with data accuracy and reliability. How should data quality tools be implemented to address these issues?
- Apply data quality tools only after data is loaded
- Embed data quality checks throughout the ETL process
- Implement data quality tools at the extraction phase
- Integrate data quality tools at the loading phase
Data quality tools should be embedded throughout the ETL process, ensuring accuracy and reliability from extraction to loading. This approach helps in identifying and addressing issues at every stage of the data flow.
Loading...
Related Quiz
- What is the primary purpose of data transformation in the ETL process?
- In advanced ETL testing, what is the impact of data transformation rules on test requirement analysis?
- How often should regression testing be performed in a typical ETL process?
- In ETL testing, what is the primary goal of transformation testing?
- How does indexing a database table affect query performance?