ITS 632 Module Five Essay Guidelines and Rubric

Topic: Cluster analysis: challenges, trends, and tools

Overview: The purpose of this assignment is to explore the current challenges, trends, and tools that are associated with the process of
conducting a cluster analysis.

Data storage used to be the biggest challenge with big data. However, due to advances in cloud infrastructures, storing data is no longer a key
concern. Accessing data is now the newest imperative that data scientists face today. Clustering has made big data analysis much easier.
However, clustering has introduced its own set of challenges that data engineers must address.

 Primary challenges with data clustering. Describe and explain one or two of the primary challenges associated with data clustering
techniques. For example, selecting the correct algorithm for the analysis can be difficult. The literature on cluster analysis includes
thousands of different algorithms that can be used. Finding the right one for a particular problem requires expertise in the myriad of
mathematical and computational options that are available.

 Current trends in technology for mitigating challenges. Please describe one trend in data science that can help organizations overcome
today’s data clustering challenges. For example, hierarchical clustering has gained traction with machine learning because it does not
require the data scientist to pre-specify the number of clusters.

 Data mining tools. Describe one tool that can support the process of data clustering and provide a real-world example or scenario where
this tool has helped an organization overcome their data clustering challenges. For example, the open source tool Weka has a Cluster
panel that can be used to identify attributes of those banking customers who have been most loyal for distributing specialized digital
marketing campaigns.

Guidelines for Submission: Using APA 6th edition style standards, submit a Word document that is 2-4 pages in length (excluding title page,
references, and appendices) and include at least two credible scholarly references to support your findings. The UC Library is a good place to find
these sources. Be sure to cite and reference your work using the APA guides and essay template that are located in the courseroom.

Include the following critical elements in your essay:

I. Primary challenges: Describe and explain one or two of the primary challenges associated with data clustering techniques that the modern
organization or data scientist face in the current data mining environment.

II. Current trends: Describe one current trend in data science that can help organizations overcome today’s data clustering challenges.

III. DM tools and real-world scenario: Describe one tool that can support the process of data clustering and provide a real-world example or
scenario where this tool has helped an organization overcome their data clustering challenges.

Required elements:
 Please ensure your paper complies APA 6th edition style guidelines. There is an essay template located under the Information link.
 APA basics:

o Your essay should be typed, double-spaced on standard-sized paper (8.5″ x 11″)
o Use 1″ margins on all sides, first line of all paragraphs is indented ½” from the margin
o Use 12 pt. Times New Roman font
o Include and introduction and conclusion (at least one paragraph)

 Follow the outline provided above and use section headers to improve the readability of your paper. If I cannot read and understand it,
you will not earn credit for the content.

Critical Elements Proficient (100%) Needs Improvement (70%) Not Evident (0%) Value

Primary challenges
Explains the primary challenges
associated with data clustering.

Description of challenges lacks
substantive explanation.

Did not explain the primary
challenges with data clustering.

30

Current trends
Explains current data clustering
trends that address the challenges.

Description of the current trends in
data clustering to resolve the
challenges lacks substantive
explanation.

Did not provide a valid
description of the current trends
in data clustering to resolve the
challenges.

30

DM tools and real-world
example

Described one tool that can support
the process of data clustering and
provided a real-world example or
scenario of how the tool is used.

Described one data clustering tool
but did to provide a valid scenario or
example. Description lacks
substantive details.

Did not describe one tool and did
not provide a scenario or
example of how the tools is used.

30

Articulation of Response
Submission has no major errors
related to citations, grammar,
spelling, syntax, or organization.

Submission has major errors
related to citations, grammar,
spelling, syntax, or organization that
negatively impact readability and
articulation of main ideas.

Submission has critical errors
related to citations, grammar,
spelling, syntax, or organization
that prevent understanding of
ideas.

10

EARNED TOTAL 100%