Join Doug Rose for an in-depth discussion in this video Ignore business value, part of Learning Data Science: Using Agile Methodology.
- Even when your team finds something interesting,…you still have to connect it to real business value.…It's not easy to connect exploration to business value.…Often in data science, you don't know the business value,…until after you've found the insight.…You have to go through the entire life cycle,…before you can deliver anything interesting.…That's one of the key benefits of working in sprints.…You'll deliver stories a little bit at a time,…every two weeks.…Each sprint, you'll build on what you know.…The research lead can evaluate your insights…and connect it to real business value.…
If the team is on the wrong path,…then they can pivot to something more interesting.…I once worked for a retailer,…that was trying to improve their worker safety.…They created a Hadoop cluster,…that collected all of their unstructured data.…The cluster had video, images, and injury reports.…The data science team used this data to create a word cloud…of all the organization's job injuries.…Then the team presented the cloud…at their storytelling session.…
This course shows how to structure your work within a two-week sprint. See how to work within a data science life cycle (DSLC)—a methodology for cycling through questions, research, and reporting every two weeks. Explore key practices to help your team break down the work so it fits within a two-week sprint. Learn how to use tools like question boards to encourage discussion and find essential questions. And most importantly, learn how to grow your team's shared knowledge and avoid common pitfalls.
- Defining data science success
- Determining project challenges and criteria for success
- Using a DSLC
- Iterating through DSLC sprints
- Creating a question board
- Breaking down your work
- Adding to organizational knowledge
- Avoiding pitfalls