Engineers Shouldn’t Write ETL
Engineers Shouldn’t Write ETL
3/19/2016
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summary
In this blog post, the author argues against engineers writing ETL (Extract, Transform, Load) code. They make the case that ETL is a distinct discipline that requires different skills and expertise than general software engineering. The author suggests that engineers should focus on building robust and scalable systems, while ETL specialists can focus on designing efficient data pipelines. The post also highlights the limitations and risks of engineers taking on ETL responsibilities, such as decreased productivity and increased likelihood of errors. Ultimately, the author emphasizes the importance of recognizing the specialized nature of ETL and leveraging the expertise of dedicated ETL professionals.
tags
data engineering ꞏ etl (extract ꞏ transform ꞏ load) ꞏ data pipelines ꞏ software engineering ꞏ data processing ꞏ data integration ꞏ data transformation ꞏ data architecture ꞏ data modeling ꞏ data analysis ꞏ data infrastructure ꞏ data warehousing ꞏ data management ꞏ software development ꞏ data analytics ꞏ data science ꞏ data-driven ꞏ coding best practices ꞏ software design ꞏ data extraction ꞏ data manipulation ꞏ data ingestion ꞏ data quality ꞏ data governance ꞏ data storage ꞏ data validation ꞏ data migration ꞏ data lineage ꞏ data cleaning ꞏ data normalization ꞏ data aggregation ꞏ data engineering tools ꞏ data engineering frameworks ꞏ data engineering workflows ꞏ big data ꞏ data scalability ꞏ data performance ꞏ data operations ꞏ cloud computing ꞏ distributed systems ꞏ software testing ꞏ software deployment ꞏ data reliability ꞏ data security ꞏ scalability ꞏ system optimization ꞏ data privacy