Evolving Methodologies
The crisp-dm methodology, established in the 1990s, remains the most recognized framework in data science, yet it faces limitations that hinder its evolution. Practitioners often struggle to articulate their methodologies, leading to a lack of standardization in the field. A recent survey aims to gather empirical data on how data science is applied in industry, highlighting the need for updated practices in response to emerging technologies and challenges.In this clip
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Data Skeptic
A Survey of Data Science Methodologies
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