The Art of Abstraction in ETL: Keeping The Good Things Going

Maintaining a robust data ingestion process requires adopting best practices from software engineering and devOps, including reproducibility, automation and orchestration, and observability. Reproducibility ensures that the same inputs are provided to data jobs consistently, while automation and orchestration provide ways to execute jobs when needed and trigger downstream tasks based on upstream task completion. Observability allows monitoring of jobs to ensure they ran as intended. To achieve these goals, version control tools like git and platforms like GitHub can be used for tracking changes to project code and configurations over time. Additionally, maintaining consistent package versions helps keep the system running as intended. Automating data ingestion processes with scheduling or orchestration tools ensures that jobs run precisely when needed and in the correct order. Observability requires notifications, logging infrastructure, and monitoring of ingested data for quality issues to enable rapid problem-solving when failures occur. By embracing devOps best practices, data teams can reliably deliver high-quality data with lower maintenance overhead and unforeseen issues.

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