Creating a robust CI/CD process for ETL pipelines in AWS
We now know that CI/CD helps maintain high-quality software through automated testing and continuous integration. But how does that specifically apply to ETL data pipelines? Here, we’ll provide brief examples of how automated testing reduces the chance of introducing bugs, facilitates early detection, and resolves integration issues in ETL data pipelines using AWS resources:
- Data warehousing: ETL processes are often used to pull data from several disparate sources and compile it into a single accessible warehouse
- Data migration: Companies undergoing digital transformation processes often use ETL pipelines to move data from old systems to new ones
- Data cleaning: ETL pipelines can be employed to clean, validate, and standardize data, ensuring it’s in the right format for further analysis or processing
Let’s put this into practice and create a CI/CD pipeline using tools within AWS.
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