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DSCI 2010 Walden University Nutri Mondo and Data Deployment Project

 

In this week, you continue to play the role of
an intern at Nutri Mondo, an organization that uses data science to
address issues related to food insecurities and other food-related
issues. Read the message from the director of Nutri Mondo, Susana
Maciel, to set the context for your assignment.

SUBJECT: REPORTS
FROM: SUSANA.MACIEL@NUTRIMONDO.ORG
TO: YOU

Hello,

You have been doing a great job of keeping me up to date on this
project. I really think you have a knack for this! I sure hope you have
enjoyed your internship. I will need to lean on you a bit more at this
next stage of the project. I would like your views on how we should
deploy the visualizations created by the data science team with the
departments who will be using them in their work with communities. The
team will give you some options, and I would like you to let me know
what you think. Whatever we decide, make sure the team covers how they
use feedback to improve their visualizations. This is where our local
teams’ understanding of how we work with communities can educate our
data scientists on how we can apply what they are providing to us.

It has been a real pleasure working with you on this project, and I hope
you found it fruitful. Who knows, after you get your certificate, maybe
you will come work for us! I look forward to reading your final
reports.

Best wishes,

Susana Maciel
Director
Nutri Mondo

To prepare for this
assignment, review this week’s Learning Resources. Then write a report
for your director to provide the following:

  • Explain the different ways that the data science team at Nutri Mondo could deploy what they have found in the data?
  • If the decision were yours to decide, explain how you would deploy
    the data. You may combine or edit the options presented Nutri Mondo for
    you answer. Explain your reasoning.
  • Summarize the feedback the data science team are receiving from
    others in the organization. Include how the feedback is providing
    insights for the data science team to refine their model.