Operationalizing Data Science
Brian emphasizes the importance of integrating operationalization into the design of data solutions from the outset. He critiques the tendency of some data scientists to create technically sound models that ultimately go unused, highlighting the need for a focus on outcomes rather than just features. By advocating for the role of data product managers, he underscores the necessity of identifying and addressing the underlying problems that data solutions aim to solve.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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