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Applied Sciences homework help

Instead of assigning a traditional exam for your “Final Exam”, you will demonstrate your understanding of the importance of the final two phases of the Data Analytics Lifecycle: Communicating the Results and Operationalizing. You have studied various analytic methods, along with surveying various available tools and techniques. But as a Data Scientist, you must also communicate what your team has accomplished.

For your Final “Exam”, you will create a Final Sponsor Presentation. You have been hired by Aetna to use big data to improve patient health. The case study you will use can be found at: https://gigaom.com/2012/11/20/how-aetna-is-using-big-data-to-improve-patient-health/ .

Your assignment is to take this case study and create a PowerPoint Presentation of the Final Sponsor Presentation, as described in Chapter 12 of your text. (Make sure to use the format presented in Chapter 12.)

You will submit a PowerPoint Presentation file (ppt or pptx) with at least the following slides: (You can submit more, but I’m mainly looking for these six slides)

  1. Title (Your name + other info)
  2. Situation and Project Goals
  3. Executive Summary
  4. Approach
  5. Method Description
  6. Recommendations

Note: There is no direct information in the case study that covers the specific analytics methods used. You will extrapolate from the provided information in the case study and provide your own interpretation of the method (or methods) the Data Science team used. Draw from what we have covered this semester and map what you learned to what that team probably did. There is no rubric for this assignment. I want you to be as creative as possible. Tell the story. Inspire your sponsors.

Text book : MC Education Service (Eds). (2015) Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing, and Presenting Data, Indianapolis, IN: John Wiley & Sons, Inc.

Chapter 12, “The Endgame, or Putting It All Together”

Link : http://index-of.co.uk/Big-Data-Technologies/Data%20Science%20and%20Big%20Data%20Analytics.pdf

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