From the course: Problem Identification and Solution Design for Data Scientists
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Leveraging IT experience and expertise
From the course: Problem Identification and Solution Design for Data Scientists
Leveraging IT experience and expertise
- [Instructor] Data science in general, and predictive analytics specifically often require more data and more granular data than your typical data request. IT and data engineering teams work very hard to anticipate routine requests to reduce the volume of unique one-off requests. And here comes along the predictive analytics project, and nothing about it is seemingly routine. If you aren't careful, they might dread emails from you. With the rise of the data engineering specialty, these teams will know more and more about the needs of these projects, as there is greater overlap and skillset than ever before between data engineering teams and data science teams. So they'll understand why this is necessary. Nonetheless, this is a critical relationship, so you'll want to nurture it. My advice is to not assume that they have been very well-informed about the project. They've probably been informed of a request and that someone important, the project sponsor or the project sponsor's boss…
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