Computer Science

University of the Cumberlands

School of Computer and Information Sciences

Instructor: Dr. Yehia Mohamed

Class: ISOL536-Security Architecture and Design

Assignment: Week 5 Residency Group Presentation

Abstract: Minimum of 250 words

Power Point Slides: 8 slides

Due date: Sunday, February 09, 2020

Briefly respond to all the following questions. Make sure to explain and backup your responses

with facts and examples. This assignment should be in APA format and have to include at least

two references.

Study the enterprise architecture for a moment and consider the implications of each of the

functions represented. Do presentation layers add an attack surface to the enterprise? How about

an eCommerce presence? The supply chain will interact with an entire business ecosystem of

many other organizations. Interactions will probably include both people and automated flows.

Are these third parties to be trusted at the same level as the internal systems, such as content

management or data analysis? Going a step further, are there threat agents whose goals include

the business data of the organization? If so, does that make the business analysis function or the

content management systems targets of possible interest? Why?

 

QUESTION 1

What are the three characteristics of Big Data, and what are the main considerations in processing Big Data?

 

QUESTION 2

Explain the differences between BI and Data Science.

 

QUESTION 3

Briefly describe each of the four classifications of Big Data structure types. (i.e. Structured to Unstructured)

 

QUESTION 4

List and briefly describe each of the phases in the Data Analytics Lifecycle.

 

QUESTION 5

In which phase would the team expect to invest most of the project time? Why? Where would the team expect to spend the least time?

 

QUESTION 6

Which R command would create a scatterplot for the dataframe “df”, assuming df contains values for x and y?

 

QUESTION 7

What is a rug plot used for in a density plot?

 

QUESTION 8

What is a type I error? What is a type II error? Is one always more serious than the other? Why?

 

QUESTION 9

Why do we consider K-means clustering as a unsupervised machine learning algorithm?

 

QUESTION 10

Detail the four steps in the K-means clustering algorithm.

 

QUESTION 11

List three popular use cases of the Association Rules mining algorithms.

 

QUESTION 12

Define Support and Confidence

 

QUESTION 13

How do you use a “hold-out” dataset to evaluate the effectiveness of the rules generated?

 

QUESTION 14

List two use cases of linear regression models.

 

QUESTION 15

Compare and contrast linear and logistic regression methods.

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