What are the best practices for ensuring data quality in ETL processes?
An example of an AI chatbot conversation about data quality in ETL processes.
What are the best practices for ensuring data quality in ETL processes?
To ensure data quality in ETL processes, you should implement data validation, cleansing, and monitoring.
Can you explain what data validation involves?
Data validation involves checking the accuracy and quality of data before it is processed, ensuring it meets predefined criteria.
What tools can I use for data cleansing?
Popular tools for data cleansing include Talend, Informatica, and Apache Nifi, which help automate the cleansing process.
How can I monitor data quality over time?
You can monitor data quality by setting up automated reports, dashboards, and alerts to track data anomalies and trends.
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