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Agile for Data Science

Topic: Agile

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Agile Data Projects

Apply agile to data work.

Sprints

Two-week sprints. Sprint planning: select work. Daily standups: blockers. Review: demo work. Retrospective: improve.

User Stories

As a [user], I want [feature], so that [benefit]. Acceptance criteria: what must work.

Challenges

Exploratory nature. Data dependencies. Hard to estimate. Integration with other teams.

Key Takeaways

  1. Sprints provide structure
  2. User stories focus on value
  3. Adapt agile for data context

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