Question 1 6 pts) Assume the following data about a


Question 1 

6 pts) Assume the following data about a student. (6pts) 

Student_ID : 1234 

Name : First name : Sidney

Last name : Prescott

Academics: Major : Criminology GPA : 3.8 

Using the studentID as identifier, illustrate how you would store the data using 

a) Key-value store (3 pts) 

b) Wide-column store (3 pts) 

You can use similar illustrations as in the textbook/slides. 

Question 2 (6 pts) 

In class, we discussed the use of MapReduce in a words count scenario. Using your own words, write a short explanation of how the MapReduce framework can be used to count the number of occurrence of each words within a large paragraph. 

Your explanation should contain the various MapReduce components discussed in class with indication on the task of each of the components. 

Question 3 

(8 pts) For each of the situations described below, select the type of analytics that would address the specific organizational need and justify your selection. 

(8pts) a. To support staffing analysis for a holiday season, a clothing store wants to improve its understanding of the number of customers that are likely to visit each of its stores during the November 15–January 15 time frame. 

b. A virtual assistant AI, such as Siri or Alexa, keeps asking its user for feedback about the AI response to specific user voice commands. The objective is for the AI to automatically tune its voice recognition components and improve the accuracy of its future responses based on the user feedback. 

c. For a class project, a student searches the different factors which contribute to heavy migration of population during the 20th century. The student will likely derive tables and graphs showing and comparing the influence of these factors between various periods of high migration. 

d. A couple wants to travel for the upcoming holidays seasons. However, with flight prices always fluctuating, they are having a hard time deciding when is a good time to purchase those tickets. Since they both have data analysis skills, they decide to analyze the last 3 years prices changes in order to hopefully find out a pattern and derive the best day to buy their tickets this year

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