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
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?
What are the three characteristics of Big Data, and what are the main considerations in processing Big Data?
Explain the differences between BI and Data Science.
Briefly describe each of the four classifications of Big Data structure types. (i.e. Structured to Unstructured)
List and briefly describe each of the phases in the Data Analytics Lifecycle.
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?
Which R command would create a scatterplot for the dataframe “df”, assuming df contains values for x and y?
What is a rug plot used for in a density plot?
What is a type I error? What is a type II error? Is one always more serious than the other? Why?
Why do we consider K-means clustering as a unsupervised machine learning algorithm?
Detail the four steps in the K-means clustering algorithm.
List three popular use cases of the Association Rules mining algorithms.
Define Support and Confidence
How do you use a “hold-out” dataset to evaluate the effectiveness of the rules generated?
List two use cases of linear regression models.
Compare and contrast linear and logistic regression methods.