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For this Assignment, you will return to your role as 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,  Thank you for keeping me up to date on how the data understanding and data preparation phases were going. I am assuming that I will get to see some visualizations soon on the effects of food insecurity. Please let me know how they evaluate the models they are building. It will help me understand some of the models that they ultimately go with. Also, I know that this data set is from the U.S. government. We work with several communities across Latin America and South America regarding food insecurity and other similar issues. I would be curious to know if you would like to find a data set related to an issue that affects your community. Of course, if you have other interests, I would like to know what challenges you would like to solve with data science. Later on, you can send me any data visualizations that you find interesting. Looking forward to your reports, Regards, Susana Maciel Director Nutri Mondo   To prepare for this assignment, review this week’s Learning Resources. Then write a report to your director about data modeling and how to evaluate models. Your report must answer the following: What is the purpose of data modeling and what does it accomplish? Why does modeling come after data scientists understand and prepare their data? How does a data scientist ensure that modeling responds to the original business understanding? What were the processes that the data science team at Nutri Mondo is using to evaluate the models they created? Your report should be 8–10 paragraphs in length. Learning Resources Required Readings Hammond, K. J. (2013, May 1). The value of big data isn’t the data. Harvard Business Review Digital Articles. Translated and reprinted by permission of Harvard Business Publishing. This article was originally published under the English title, “The Value of Big Data Isn’t the Data,” by Hammond, K. J. in the issue May 1. Copyright 2013 by the Harvard Business Publishing Corporation; all rights reserved. This translation, Copyright 2018 by the Harvard Business Publishing Corporation.   Read this data to understand the importance of using data to tell a story. Li, M. (2015, October 13). The best data scientists know how to tell stories. Harvard Business Review Digital Articles. Translated and reprinted by permission of Harvard Business Publishing. This article was originally published under the English title, “The Best Data Scientists Know How to Tell Stories,” by Li, M. in the issue Oct. 13. Copyright 2015 by the Harvard Business Publishing Corporation; all rights reserved. This translation, Copyright 2018 by the Harvard Business Publishing Corporation.   Read this article to understanding why it is important for data scientists to have technical skills and the ability to communicate the story behind the data. Veeramachaneni, K. (2016, December 7). Why you’re not getting value from your data science. Harvard Business Review Digital Articles. Translated and reprinted by permission of Harvard Business Publishing. This article was originally published under the English title, “Why You’re Not Getting Value from Your Data Science,” by Veeramachaneni, K. in the issue Dec 7. Copyright 2016 by the Harvard Business Publishing Corporation; all rights reserved. This translation, Copyright 2018 by the Harvard Business Publishing Corporation.   Read this article to learn how businesses can get value from their data repositories with machine learning. Required Media IBM. (2016p). Modeling – Concepts [Video file]. Armonk, NY: Author.   Note: The approximate length of this media piece is 3 minutes.   Watch this video from IBM about how data scientists approach the data modeling step of the data science methodology.   Accessible player  –Downloads– Download Video w/CC Download Audio Download Transcript IBM. (2016o). Modeling – Case study [Video file]. Armonk, NY: Author.   Note: The approximate length of this media piece is 4 minutes.   Watch this video from IBM to see how data scientists create a predictive model for a data science project.   Accessible player  –Downloads– Download Video w/CC Download Audio Download Transcript IBM. (2016k). Evaluation [Video file]. Armonk, NY: Author.   Note: The approximate length of this media piece is 4 minutes.   Watch this video from IBM to see some of the processes and tools that data scientists use to evaluate a predictive model.   Accessible player  –Downloads– Download Video w/CC Download Audio Download Transcript Laureate Education (Producer). (2018a). Case study: Data modeling [Video file]. Baltimore, MD: Author.   In the World of Data Science, visit Tegucigalpa and view the Data Modeling video. Watch a data science team evaluate some of the descriptive models they have created for their project. Optional Resources TedGlobal. (2010, July). David McCandless: The beauty of data visualization [Video file]. Retrieved from https://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization?utm_campaign=tedspread&utm_medium=referral&utm_source=tedcomshare