There’s no single data science project documentation recipe. Rather, your documentation needs will vary by project, team, organization, and industry. And it’s not just about producing data science model documentation. Instead, think broader and ask – What do I need to document and why? Once you’ve thought this through and […]Read more
A data science strategic plan isn’t just about data. Rather, it is a comprehensive plan that defines how you build and maintain an ecosystem that delivers sustainable value from your data science investments.
Developing this plan is not easy. So why bother?
Well, without one, you could be steering down a path without knowing where it is going…Read more
The demands for data science insights and systems far outstrip the capacity for data science teams to deliver. How do you best balance this? Enter the Data Science Product Manager. Unlike more tactical roles like the project manager who oversees the project life cycle or a process master who drives […]Read more
Based on my personal experience, below are the 8 key data science team roles to think about when building and leading a data science team. These are not in any specific order, as their importance might vary from one project to another, or from one organization to another. Furthermore, not […]Read more
Data science projects are challenging. To increase your odds of success, start them by asking several key data science project questions. As Ben Franklin said, “an ounce of preparation saves a pound of headaches in your data science projects”.* To help you prepare for a project and evaluate whether to […]Read more
What can you learn if you observe data science teams across 20 large companies? I asked Mac Steele, Director of Product at Domino Data Lab, to find out. Mac combined the lessons he learned from observing data science teams with concepts from CRISP-DM and agile to create the Domino Data Science Lifecycle Domino […]Read more