The original title is "Data Engineering: The Data Field's Unknown Child"

Short summary

An explainer on data engineering as the foundational infrastructure layer that enables data science and analytics. Data engineers build pipelines to collect, clean, and store data — analogous to plumbers ensuring clean water flows on demand. The article argues that bad data engineering silently corrupts all downstream insights and models, making it critical for any company beyond the spreadsheet stage or investing in AI/ML.

• •Data engineers build pipelines that collect, clean, and store data for analysts and scientists
• •Bad data engineering silently poisons all downstream analytics and ML models
• •Most critical for companies with multiple data sources, AI/ML investments, or regulated industries

Generated with AI, which can make mistakes.