From the course: Learning Data Science: Using Agile Methodology
Join today to access over 22,600 courses taught by industry experts or purchase this course individually.
Compare project challenges
From the course: Learning Data Science: Using Agile Methodology
Compare project challenges
- You've seen how traditional project management relies on requirements and careful planning. Remember that a typical project has scope, cost, and schedule. This isn't really compatible with the scientific method used within data science teams. Instead, data science teams are empirical and exploratory. If you insist on a plan then you're boxing the team into looking for what they already know. It's tricky to imagine a team finding new insights in a well-defined box. If you think about the meetings in most organizations, they're usually around planning and hitting objectives. The language of most organizations still hinges on phrases such as mission, objectives, and outcomes. It's difficult to step back and imagine a team of pure exploration. For most organizations, working with a data science team will be a difficult transition, so let's look at a typical project and compare it to that of a data science team. Then let's imagine what would happen if you started applying planning and…
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.