What I Love about Scrum for Data Science

A couple of years ago, I started (read: was made) to adopt scrum in my work. I didn’t like it. The concept of estimation was vague to me: How do we estimate effort for data exploration or research? And after we move something from In Progress to Done, can we move it back? This happens often (in data science) where we need to revisit an upstream step, such as data preparation or feature engineering

[el7]

データサイエンスでスクラムをやるのはオーバーヘッドがかかるものの(１スプリント3-4時間)得られるものは遥かに大きい。本当に必要な作業かを常に確認しないと前に進んでいかない