Eugene Yan argues that data scientists should adopt a more end-to-end approach to their work, encompassing problem framing, data engineering, model development, and deployment. He contends that specialization leads to coordination overhead and a loss of big-picture context, potentially resulting in suboptimal solutions. By embracing an end-to-end methodology, data scientists can better identify root causes, develop more holistic solutions, and ultimately deliver greater value. AI
RANK_REASON Opinion piece by a named author discussing a methodology in data science.
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