From the course: Problem Identification and Solution Design for Data Scientists
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Ensuring that you leave with the critical info
From the course: Problem Identification and Solution Design for Data Scientists
Ensuring that you leave with the critical info
- [Narrator] Now it's time to talk about the data with a team that has a unique perspective, the IT team, and hopefully see the actual data. Increasingly, it won't just be any member of the IT team. They are hopefully data engineers who usually have a lot of insight in data science and machine warning. I'll have more to say about not getting bogged down to delays waiting for logins and direct access later in the course. I like to meet in person and look at the data together to avoid delays. So let's assume you've been successful in doing that. This is going to be a fast moving meeting, so you have to have priorities. Here are the things I try to spot in real time. As I glance, even if just for a few seconds at a dataset for a deeper dive into this kind of data assessment. I explore these kinds of issues in greater depth with specific examples on screen and my course data science foundation's data assessment for predictive modeling. That course is quite different in style because it's…
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