Product Value in Data
Brian emphasizes the importance of creating data products that hold inherent value in the eyes of users, rather than just focusing on technical outputs. He highlights that value is subjective and often tied to the outcomes for stakeholders, such as risk management in banks. Automation is discussed, with a reminder that human oversight remains crucial, especially in unpredictable situations like model drift or external crises.In this clip
From this podcast
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658: How to Build Data and ML Products Users Love — with Brian T. O'Neill
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