Data Pipeline Essentials
Demetrios emphasizes the critical components of data pipelines, highlighting that around 50% of the effort goes into data collection and preparation. Once the groundwork is laid, the focus shifts to analytics and machine learning, which typically require about 25% of the effort. Finally, delivering insights through reports or prediction services is essential for making data accessible to end users.In this clip
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Machine in Production = Data Engineering + ML + Software Engineering // Satish Chandra Gupta // MLOps Coffee Sessions #16
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