- Tags:: 🗞️Articles , Data methodology
- Author:: Liam Kane (Senior Agile Coach in Accenture)
- Link:: Agile Data Science Part 1| The Burndown and Agile Data Science Part 2 | The Burndown
- Source date:: 2017-10-28
- Finished date:: 2021-07-30
- To make Agile work in the context of Data Science, we need to redefine what “value” means:
Value: stories that deliver demonstrable progress towards solving a business problem, from any level of the data value pyramid, ideally demonstrated to a stakeholder in a production environment for purposes of getting feedback.
- And it makes sense because we are delivering knowledge, and that is value. So an example of these “new” user stories are:
Example: As a project stakeholder, I want to see the results of an EDA, so that I am confident that we understand the primary drivers of customer churn rate.
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I will need multiple Definitions of Done (one for EDAs, other for modeling…)
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There is a reference here to the 📖 Agile Data Science 2.0 book.