Data Science and Agile (Frameworks for Effectiveness)
Read OriginalThis article analyzes how Agile and Scrum methodologies can be effectively applied to data science projects. It details what works well (e.g., periodic planning, retrospectives) and what doesn't (e.g., difficulty with estimations, changing scope). The author provides practical frameworks and adaptations, like time-boxed experiments and innovation time, to improve data science team productivity and alignment with business goals.
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