How do you ensure Data quality in data pipelines

Question

Accepted Answer

Data quality in data pipelines is ensured through data validation, monitoring, cleansing, and transformation.

Perform data validation checks at each stage of the pipeline to ensure accuracy and completeness.
Implement monitoring tools to track data quality metrics and identify issues in real-time.
Use data cleansing techniques to remove duplicates, correct errors, and standardize formats.
Apply data transformation processes to ensure consistency and compatibility across different sources.
Regularly audit and review data pipelines to maintain high quality standards.
Example: Implementing automated tests to validate data integrity before loading into the data warehouse.

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