Join Doug Rose for an in-depth discussion in this video Tell an interesting story, part of Data Science Teams: Doing Agile Data Science.
- There's a big difference between presenting data…and telling a story.…For one thing, telling a story is much more challenging.…It requires a lot more work.…You're combining the data with what you know…about the business.…Then you're relating your insights…to what you know about the world.…When you put up a data PowerPoint presentation,…you're saying, "Here's what I see."…When you're telling a story, you're saying,…"Here's what I believe."…That's a much more difficult thing to do.…In a way it's also more personal.…That's why storytelling is such a valuable skill.…
In a modern office, almost anyone can create a chart…using Microsoft Excel.…People think of this in the same way…as knowing how to use a computer.…When you're telling a story,…you're doing several things at once.…The first thing you're doing is synthesizing…much of the complexity in your data.…You're explaining something that's complex…in a simpler way.…You're also defining the motivations…of the people who are involved in creating this data.…The second thing you're doing is bringing…
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