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Data Science: Mindset, Methodologies, and Misconceptions by Zacharias Voulgaris PhD

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Chapter 2 The Data Science Pipeline

Contrary to what many people think, the whole process of turning data into insights and data products is not at all straight-forward. In fact, it’s more of an iterative process, with impromptu loops and unexpected situations causing delays and reevaluations of your assumptions. That’s why we often talk about the data science pipeline, a complex process comprised of a number of inter-dependent steps, each bringing us closer to the end result, be it a set of insights to hand off to our manager or client, or a data product for our end-user. This whole process is organized in three general stages: data engineering, data modeling, and information distillation (this last one is a term coined by me). Each of these ...

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