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Answer: Implementing data validation tests at each stage of the pipeline, Conducting regular audits of the data processing logic and outputs
**Correct Options: A. Implementing data validation tests at each stage of the pipeline and E. Conducting regular audits of the data processing logic and outputs** Data validation tests are crucial for ensuring the accuracy, completeness, and consistency of data as it moves through the pipeline. Regular audits complement these tests by providing an additional layer of oversight, ensuring that the pipeline adheres to regulatory standards and maintains data integrity over time. **Why Other Options Are Incorrect:** - **B. Reducing the level of data encryption:** This compromises data security, which is critical for sensitive financial data, and does not directly improve data quality. - **C. Disabling auto-scaling features:** While this may reduce costs, it does not address data quality and could lead to performance issues during peak loads. - **D. Increasing the computational resources allocated to the pipeline:** This may improve performance but does not inherently ensure data quality or compliance with regulatory standards.
Author: LeetQuiz Editorial Team
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In the context of implementing changes to a data processing pipeline, which methods are essential for maintaining data quality? Consider a scenario where the pipeline processes sensitive financial data requiring high accuracy and compliance with regulatory standards. Choose the two most effective methods from the options provided.
A
Implementing data validation tests at each stage of the pipeline
B
Reducing the level of data encryption to speed up processing times
C
Disabling auto-scaling features to reduce operational costs
D
Increasing the computational resources allocated to the pipeline
E
Conducting regular audits of the data processing logic and outputs
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