From the course: Learning Data Science: Using Agile Methodology
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Iterate through DSLC sprints
From the course: Learning Data Science: Using Agile Methodology
Iterate through DSLC sprints
- Now that you've seen a data science life cycle, you might be wondering how this looks in practice. One of the most important things to remember about the DSLC is that it's not designed to run in phases. The DSLC is about focusing on five key areas. It starts off by identifying the key players in your story. Then you go through a loop of questions, research, and results. You look for insights and then add to organizational knowledge. This whole life cycle can be run in a short sprint. You may have hard the term sprint. It's widely used in agile software, but it actually came from product development. A sprint is a fixed period of time where the team runs through the entire life cycle. Each sprint should run all five areas of the DSLC in this fixed time. The data science team can run in two week sprints. That's long enough to find insights, and yet still short enough to adapt to new ideas. The main advantage of running in sprints is that that it shortens the time between concept and…
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