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CWC
Project Name: Click here to enter text.
Project
Topic: This project will
examine datasets on artificial intelligence and its impact on the healthcare
ecosystem.
Research
Question: What is the impact of artificial intelligence on healthcare?
Hypothesis: Adopting artificial
intelligence will positively impact the healthcare system.
Context:
Artificial
Intelligence can help doctors and medical providers deliver more accurate
diagnoses and treatment plans. Using AL software and hardware can help make
healthcare more predictive and proactive by analyzing big data to develop
improved patient preventive care recommendations.
Data:
Identify data you will need to collect that are relevant to the
situation or question.
Click here to enter text.
If an existing dataset will be used, describe
the dataset. Click here to enter
text.
Explain who owns the data and why you
are allowed to use the data for your capstone project. Click here to enter text.
Note: If you are using restricted
information, please have the “Authorization to Use Restricted Information” form
signed by an authorized agent on behalf of the data owner. The data owner’s
legal name is required on the form.
Data Gathering: Describe the data-gathering
methodology you will use to collect data. Click here to enter text.
Data Analytics Tools and Techniques: Identify the appropriate data-analysis
technique you will use to analyze the data. Click here to enter text.
Justification
of Tools/Techniques: Explain
why the data-analysis technique you chose is an appropriate technique to
analyze the data collected. Click here to enter text.
Application
Type, if applicable (select one):
☐ mobile
☐ web
☐ stand-alone
Programming/Development
Language(s), if applicable:
Click here to enter text.
Operating
System(s)/Platform(s), if applicable: Click here to enter text.
Database
Management System, if applicable: Click here to enter text.
Project
Outcomes: List the key anticipated project outcomes
and deliverables in fewer than 500 words. Click here to enter text.
Projected
Project End Date: Click here to enter a date.
Sources: Click here to enter text.
Human
Subjects or Proprietary Information
Does your project involve the potential
use of human subjects? (Y/N): N
Does your project involve the potential
use of proprietary company information? (Y/N): N
TASK 2: PROJECT PROPOSAL
COMPETENCIES
Capstone
The learner
integrates and synthesizes competencies from across the degree program, thereby
demonstrating the ability to participate in and contribute value to the chosen
professional field.
INTRODUCTION
This task will
consist of a proposal for a data analytics project that was approved by an
instructor. The proposal will identify a problem and propose a data solution to
the problem. Your proposal will also explain how you plan to implement your
project to successfully resolve the problem, including a methodology for
project development.
Your work for Task 2 will not be evaluated until the appropriate forms in Task
1 have been submitted and evaluated.
REQUIREMENTS
Your submission must
be your original work. No more than a combined total of 30% of the submission
and no more than a 10% match to any one individual source can be directly
quoted or closely paraphrased from sources, even if cited correctly. The
similarity report that is provided when you submit your task can be used as a
guide.
You must use the rubric to direct the creation of your submission because it
provides detailed criteria that will be used to evaluate your work. Each
requirement below may be evaluated by more than one rubric aspect. The rubric
aspect titles may contain hyperlinks to relevant portions of the course.
Tasks may not be submitted as cloud links, such as links to
Google Docs, Google Slides, OneDrive, etc., unless specified in the task
requirements. All other submissions must be file types that are uploaded and
submitted as attachments (e.g., .docx, .pdf, .ppt).
Project Overview
A. Create
a proposal for a data analytics project by doing the following:
1. Describe
a research question or organizational need that your project will solve.
2. Describe
the context and background for your project.
3. Summarize three published
works that relate to the research question or organizational need in part A1.
Note: These published works should
serve as background information to support your proposed project and may
include interviews, white papers, research studies, or other types of work by
industry professionals.
a. Describe
how each published work informs the development of the
project.
4. Describe
the deliverables (e.g., reports, visuals, apps, or models) for the data analytics
solution you will implement to address the research question or organizational
need described in part A1.
5. Explain how
the data analytics solution will benefit the organization and support a
decision-making process.
Data Analytics
Project Plan
B. Describe
your data analytics project plan by doing the following:
1. Describe
the goals, objectives, and deliverables for the project.
2. Describe
the scope of the project.
3. Explain
how you will use a project planning methodology (e.g., ADDIE, SDLC, Agile,
CRISP-DM, or SEMMA) to organize and implement your project.
4. Provide
a timeline with milestones for your project, including the duration and start
and end dates for each milestone.
5. Provide
a list of resources and any associated costs needed to
implement the project (e.g., hardware, software, work hours, third-party
services).
6. Describe
the measurable criteria you will use to evaluate the success of project
execution.
Design of Data
Analytics Solution
C. Describe
the data analytics solution you will use to address the research question or
organizational need identified in part A by doing the following:
1. Identify
the hypothesis of the project.
2. Identify
the analytical methods (i.e., descriptive, diagnostic, predictive, or
prescriptive) you will implement in your data analytics solution.
a. Justify
why the analytical methods identified in part C2 are appropriate for your
project.
3. Describe
the tools and environments that you will use to produce the data analytics
solution, including any applicable third-party code.
4. Describe
the methods and metrics you will use to evaluate the output of your data
analytics solution or model.
a. Justify
why the chosen methods and metrics are appropriate for evaluating the output of
your data analytics solution or model.
5. Describe
how you will assess the practical significance of the data analytics solution,
including specific criteria to determine whether it has provided the expected
benefits and supported a decision-making process.
6. Describe
the tools and graphical representations you will use to visually communicate
the findings of your data analytics solution.
Description of
Dataset(s)
D. Write
a description of the data by doing the following:
1. Identify
the source(s) of the data.
2. Discuss
why this dataset is appropriate for the stated goals of your project.
3. Describe
the data collection methods you used.
4. Summarize
your observations on the quality and completeness of the data.
5. Discuss
data governance; data privacy and security; and ethical, legal, and regulatory
compliance considerations that relate to the dataset and the proposed project.
a. Describe
the precautions you will need to take when working with and communicating about
the data for each of the considerations in part D5.
E. Acknowledge
sources, using in-text citations and references, for content that is quoted,
paraphrased, or summarized.
F. Demonstrate
professional communication in the content and presentation of your submission.
File
Restrictions
File name may
contain only letters, numbers, spaces, and these symbols: ! – _ . * ‘ ( )
File size limit: 200 MB
File types allowed: doc, docx, rtf, xls, xlsx, ppt, pptx, odt, pdf, csv, txt,
qt, mov, mpg, avi, mp3, wav, mp4, wma, flv, asf, mpeg, wmv, m4v, svg, tif,
tiff, jpeg, jpg, gif, png, zip, rar, tar, 7z
RUBRIC
A1:RESEARCH QUESTION OR ORGANIZATIONAL NEED
NOT EVIDENT
A research question or organizational need is not
described.
APPROACHING
COMPETENCE
The research question or organizational need is not
clearly described.
COMPETENT
The research question or organizational need is
clearly described.
A2:CONTEXT AND BACKGROUND
NOT EVIDENT
The submission describes neither the context nor the
background of the project.
APPROACHING
COMPETENCE
The submission does not describe the background of
the project or the context in which the project occurs. Or the description is
missing essential details, contains inaccuracies, or contains information
that is not relevant to the project.
COMPETENT
The submission accurately describes the background of
the project and the context in which the project occurs. The description
includes essential details and contains only information
that is relevant to the project.
A3:SUMMARY OF PUBLISHED WORKS
NOT EVIDENT
A summary of 3 published works is not provided.
APPROACHING
COMPETENCE
A summary of 3 different published works is provided,
but the summary of 1 or more works is missing essential details or contains
inaccuracies. Or 1 or more of the works do not relate to the research
question or organizational need in part A1.
COMPETENT
An accurate summary of 3 different published works
that relate to the research question or organizational need in part A1 is
provided, and the summary of each work includes essential
details.
A3A:RELATION OF PUBLISHED WORKS TO PROJECT
NOT EVIDENT
A description of how the 3 published works relate to
the proposed project is not provided.
APPROACHING
COMPETENCE
The description does not logically address how each published
work relates to the research question or organizational need from part A1.
COMPETENT
The description logically addresses how each published
work relates to the research question or organizational need from part A1.
A4:SUMMARY OF DELIVERABLES OF A DATA ANALYTICS SOLUTION
NOT EVIDENT
The deliverables for a data analytics solution are
not described.
APPROACHING
COMPETENCE
The described deliverables for the solution are not
appropriate for the question or need in part A1. Or they would not be able to
be realistically implemented, or they would not logically address the
question or need. Or the description is not detailed, or it contains
inaccuracies.
COMPETENT
The described deliverables for the solution are
appropriate for the question or need in part A1. They would be able to be
realistically implemented, and they logically address the question or need.
The description is detailed, and all of the information in
the description is accurate.
A5:BENEFITS AND SUPPORT OF DECISION-MAKING PROCESS
NOT EVIDENT
The submission does not explain how the data
analytics solution benefits the organization and supports the decision-making
process.
APPROACHING
COMPETENCE
The submission explains how the proposed solution
will benefit the organization or how the solution will support a
decision-making process but not both. Or the explanation is
illogical. Either the benefit or the decision-making process is unrealistic
or is unlikely to occur as a result of the proposed data analytics solution.
COMPETENT
The submission logically explains how the proposed
solution will benefit the organization and support a decision-making process.
The benefit and decision-making process are a realistic consequence of the
proposed data analytics solution.
B1:GOALS, OBJECTIVES, AND DELIVERABLES
NOT EVIDENT
The goals, objectives, or deliverables for the
project are not described.
APPROACHING
COMPETENCE
1 or more of the goals, objectives, or deliverables
are vague, unrealistic, or not logically aligned with the project. Or the
goals, objectives, or deliverables do not relate to the scope of the project
or are not aligned with each other.
COMPETENT
All of the goals,
objectives, and deliverables for the project are detailed, realistic, and
logically aligned with the project, and they relate to the scope of the
project and are aligned with each other.
B2:SCOPE OF PROJECT
NOT EVIDENT
A description of the scope of the project is not
provided.
APPROACHING
COMPETENCE
The description of the project scope does not include
what the project will or will not entail. Or the scope details do not
logically align with the goals of the project.
COMPETENT
The description of the project scope includes what
the project will and will not entail. The scope details logically align with
the goals of the project.
B3:STANDARD METHODOLOGY
NOT EVIDENT
The submission does not explain how a standard
methodology will be applied to organize and implement the project.
APPROACHING
COMPETENCE
The submission does not logically explain how a
specific project planning methodology will be used for project
implementation. Or the explanation does not include specific details on how
the methodology will organize the work. Or the methodology is not appropriate
or relevant for the implementation of the proposed project.
COMPETENT
The submission logically explains how a specific
project planning methodology will be used for the implementation of the
proposed project, including specific details on how the methodology will
organize the work. The methodology is appropriate and relevant for the
implementation of the proposed project.
B4:TIMELINE AND MILESTONES
NOT EVIDENT
A timeline with milestones is not provided.
APPROACHING
COMPETENCE
The provided timeline is missing 1 or more project
milestones or does not include the duration and start and end dates for each milestone.
Or each milestone is not logically organized or logically
sequenced by date. Or 1 or more of the milestones are unrealistic or
irrelevant to the project.
COMPETENT
The provided timeline includes all project
milestones, including the duration and start and end dates for each milestone. Each milestone
is logically organized and logically sequenced by date, and each milestone
is realistic and relevant to the project.
B5:RESOURCES AND COSTS
NOT EVIDENT
A list of resources and associated costs is not
provided.
APPROACHING
COMPETENCE
The provided list does not include all necessary
resources and all associated costs to implement the project.
Or 1 or more of the resources and costs are unrealistic or irrelevant for the
proposed project.
COMPETENT
The provided list includes all necessary
resources and all associated costs to implement the
project. All listed resources and costs are realistic and relevant
to the proposed project.
B6:CRITERIA FOR SUCCESS
NOT EVIDENT
The submission does not describe the criteria to
evaluate project success.
APPROACHING
COMPETENCE
The submission describes the criteria for evaluating
the success of project execution, but the criteria are not specific,
measurable, or relevant to the proposed project.
COMPETENT
The submission describes specific criteria for
evaluating the success of project execution, and the criteria are measurable
and relevant to the proposed project.
C1:HYPOTHESIS
NOT EVIDENT
The hypothesis of the project is not identified.
APPROACHING
COMPETENCE
The hypothesis is not clearly stated or is not
aligned with the research question or organizational need identified in part
A1.
COMPETENT
The hypothesis is clearly stated and well aligned
with the research question or organizational need identified in part A1.
C2:ANALYTICAL METHODS
NOT EVIDENT
The analytical methods of the project are not
identified.
APPROACHING
COMPETENCE
The identified analytical methods do not align with
the proposed solution.
COMPETENT
The identified analytical methods align with the
proposed solution.
C2A:JUSTIFICATION OF ANALYTICAL METHODS
NOT EVIDENT
The submission does not justify the chosen analytical
methods.
APPROACHING
COMPETENCE
The submission attempts to justify the chosen
analytical methods, but the justification does not include specific, logical
reasons for why the chosen analytical methods are appropriate for addressing
the research question or organizational need identified in part A.
COMPETENT
The submission justifies the chosen analytical
methods and includes specific, logical reasons for why the chosen analytical
methods are appropriate for addressing the research question or
organizational need identified in part A.
C3:TOOLS AND ENVIRONMENTS OF SOLUTION
NOT EVIDENT
A description of the tools and environments is not
provided.
APPROACHING
COMPETENCE
The description does not include all tools
and environments used to produce the data analytics solution, or 1 or more of
the tools or environments are not relevant to the project. Or the description
is missing third-party code that should have been included.
COMPETENT
The description includes all tools
and environments used to produce the data analytics solution, and all of
them are relevant to the project. If third-party code was part of the tools
and environment, it has been included.
C4:METHODS AND METRICS TO EVALUATE OUTPUT
NOT EVIDENT
The submission does not describe the methods and
metrics used to evaluate the output of the data analytics solution or model.
APPROACHING
COMPETENCE
The submission does not accurately describe the
methods and metrics. Or the description does not include specific details on
how the methods and metrics will evaluate the output of the data analytics
solution or model. Or the description of the methods and metrics is vague or
contains inaccuracies.
COMPETENT
The submission thoroughly and accurately describes
the methods and metrics. The description includes specific details on how the
methods and metrics will evaluate the output of the data analytics solution
or model.
C4A:JUSTIFICATION OF METHODS AND METRICS
NOT EVIDENT
The submission does not justify the chosen methods
and metrics.
APPROACHING
COMPETENCE
The submission attempts to justify the chosen methods
or metrics, but the justification does not include specific, logical reasons
for why the chosen methods and metrics are appropriate for the data analytics
solution. Or the methods or metrics are poorly supported.
COMPETENT
The submission justifies the chosen methods and
metrics, including specific, logical, and well-supported reasons for why the
chosen methods and metrics are appropriate for the data analytics solution.
C5:PRACTICAL SIGNIFICANCE
NOT EVIDENT
The submission does not describe how practical
significance will be assessed.
APPROACHING
COMPETENCE
The submission does not logically describe how the
practical significance of the data analytics solution will be assessed. Or
the submission does not include specific criteria regarding whether the
solution has provided the expected benefits or supported a decision-making
process in the context of the chosen research question or organizational
need.
COMPETENT
The submission describes how the practical
significance of the data analytics solution will be assessed, including
specific criteria regarding whether the solution has provided the expected
benefits and supported a decision-making process in the context of the chosen
research question or organizational need.
C6:VISUAL COMMUNICATION
NOT EVIDENT
The submission does not describe any tools
or graphical representations for visually communicating the findings of the
solution.
APPROACHING
COMPETENCE
The submission describes the tools and the graphical
representations that will visually communicate the findings of the data
analytics solution, but the description is missing key details for 1 or more
of the described tools or graphical representations. Or the described tools
and graphical representations will not effectively communicate the expected
findings.
COMPETENT
The submission describes key details about each tool
and graphical representation that will visually communicate the findings of
the data analytics solution, and the described tools and graphical
representations will effectively communicate the expected findings.
D1:SOURCE OF DATA
NOT EVIDENT
The source of the data is not identified.
APPROACHING
COMPETENCE
Not applicable.
COMPETENT
Each source of the
data is correctly identified.
D2:APPROPRIATENESS OF DATASET
NOT EVIDENT
A discussion of why the dataset is appropriate is not
provided.
APPROACHING
COMPETENCE
The discussion does not provide reasons for why the
dataset is appropriate for the stated goals of the project.
COMPETENT
The discussion provides reasons for why the dataset
is appropriate for the stated goals of the project.
D3:DATA COLLECTION METHODS
NOT EVIDENT
The methods that were used for data collection are
not described.
APPROACHING
COMPETENCE
The described data collection methods are vague.
COMPETENT
The described data collection methods are thorough.
D4:DATA QUALITY
NOT EVIDENT
A summary of the quality and completeness of the data
is not provided.
APPROACHING
COMPETENCE
The summary includes observations on the quality or
completeness of the data but not both. Or the observations of either
the quality or completeness of the data are not logical or contain
inaccuracies.
COMPETENT
The summary includes logical and accurate
observations on both the quality and completeness of the
data.
D5:DATA GOVERNANCE; PRIVACY AND SECURITY; AND ETHICAL, LEGAL, AND
REGULATORY COMPLIANCE
NOT EVIDENT
A discussion of data governance; data privacy and
security; and ethical, legal, and regulatory compliance considerations that
relate to the dataset or project is not provided.
APPROACHING
COMPETENCE
The discussion addresses data governance; data
privacy and security; and ethical, legal, and regulatory compliance
considerations, but 1 or more of these do not relate to the dataset or the
proposed project. Or the discussion contains inaccuracies.
COMPETENT
The discussion accurately addresses the data
governance; data privacy and security; and ethical, legal, and regulatory
compliance considerations, and all of these relate to the
dataset and the proposed project.
D5A:PRECAUTIONS
NOT EVIDENT
Precautions that need to be taken are not described.
APPROACHING
COMPETENCE
1 or more of the described precautions do not include
specific details about working with and communicating about the data, or
there is not a precaution described for each of the
considerations discussed in part D5. Or 1 or more of the described
precautions do not reasonably manage the risk associated with the
considerations discussed in part D5.
COMPETENT
Each described
precaution includes specific details about working with and communicating
about the data, and there is a precaution described for each of
the considerations discussed in part D5. Each precaution
reasonably manages the risk associated with the considerations discussed in
part D5.
E:SOURCES
NOT EVIDENT
The submission does not include both in-text
citations and a reference list for sources that are quoted, paraphrased, or
summarized.
APPROACHING
COMPETENCE
The submission includes in-text citations for sources
that are quoted, paraphrased, or summarized and a reference list; however,
the citations or reference list is incomplete or inaccurate.
COMPETENT
The submission includes in-text citations for sources
that are properly quoted, paraphrased, or summarized and a reference list
that accurately identifies the author, date, title, and source location as
available.
F:PROFESSIONAL COMMUNICATION
NOT EVIDENT
Content is unstructured, is disjointed, or contains
pervasive errors in mechanics, usage, or grammar. Vocabulary or tone is
unprofessional or distracts from the topic.
APPROACHING
COMPETENCE
Content is poorly organized, is difficult to follow,
or contains errors in mechanics, usage, or grammar that cause confusion.
Terminology is misused or ineffective.
COMPETENT
Content reflects attention to detail, is organized,
and focuses on the main ideas as prescribed in the task or chosen by the
candidate. Terminology is pertinent, is used correctly, and effectively
conveys the intended meaning. Mechanics, usage, and grammar promote accurate
interpretation and understanding.
***************************************************************************************************************************************************************************************************************************************************************
THIS PORTION SHOULD BE COMPLETE AFTER VERIFICATION OF CABOVE
STEPS
TASK 3: PROJECT
REPORT
COMPETENCIES
The learner integrates and synthesizes
competencies from across the degree program, thereby demonstrating the ability
to participate in and contribute value to the chosen professional field.
INTRODUCTION
Before starting this task, ensure that
Tasks 1 and 2 have a passing score. If Task 1 or 2 has not yet passed, your
Task 3 submission will be returned without evaluation.
In this task, you will complete your capstone by writing a report that
summarizes your data analytics project, including an overview of the project, a
discussion of how the execution of your project differed from your plan, a
discussion of your project methodology, and an evaluation of your project
results. You will also submit a recorded summary of your project.
REQUIREMENTS
Your submission must be your original
work. No more than a combined total of 30% of the submission and no more than a
10% match to any one individual source can be directly quoted or closely
paraphrased from sources, even if cited correctly. The similarity report that
is provided when you submit your task can be used as a guide.
You must use the rubric to direct the creation of your submission because
it provides detailed criteria that will be used to evaluate your work. Each
requirement below may be evaluated by more than one rubric aspect. The rubric
aspect titles may contain hyperlinks to relevant portions of the course.
Tasks may not be submitted as cloud links, such as links to
Google Docs, Google Slides, OneDrive, etc., unless specified in the task
requirements. All other submissions must be file types that are uploaded and
submitted as attachments (e.g., .docx, .pdf, .ppt).
Write a report summarizing your
completed data analytics capstone project by doing the following:
Project Overview
A. Summarize the following
elements of your capstone project:
• the research question or
organizational need that your capstone addressed
• the scope of your project
• an overview of your solution,
including any tools and methodologies used
Project Execution
B. Summarize the execution of
your project, including how the execution of the following elements differed
from the plan developed in part B of Task 2:
• project plan
• project planning methodology
• project timeline and
milestones
Methodology
C. Discuss your data selection
and collection process in detail, including each of the
following elements:
• how your actual data selection
and collection process differed from your plan
• how you handled any obstacles
you encountered while collecting your data
• how you handled any unplanned
data governance issues
1. Discuss the advantages and
limitations of the dataset you used.
D. Explain your data extraction
and data preparation processes, including the tools and techniques you used,
and why these processes were appropriate for your data.
E. Report on your data analysis
process by doing the following:
1. Describe the methods you used
to analyze the data.
2. Discuss the advantages and
limitations of the tools and techniques you used to analyze the data.
3. Provide a step-by-step
explanation of how you applied the analytical methods in part E1 to the data,
including how you verified that the data satisfied the assumptions or
requirements for any analytical methods you used.
Results
F. Evaluate the success of your
data analytics project by doing the following:
1. Evaluate the output of your
data analytics solution or model, including calculations or metrics for
accuracy.
2. Evaluate the practical
significance of your data analytics solution, including specific examples.
3. Evaluate the overall success
and effectiveness of the project.
G. Summarize the key takeaways
of your analysis by doing the following:
1. Summarize the conclusions
drawn from your analysis.
2. Explain why your chosen tools
and graphical representations for visually communicating findings support
effective storytelling.
3. Recommend two courses
of action based on your findings.
H. Provide a link to a Panopto
recording in which you present a summary of your capstone project and findings
from the analysis for an audience of data analytics peers. Your summary should
include the following elements:
• a summary of your research
question or organizational need
• a demonstration of the
functionality of any code you used for your data analytics solution
• an outline of the findings and
implications of your analysis
Appendices
I. Provide evidence of project
completion by submitting any of the following elements that
are relevant to your project:
• the code you used to support
your project
• a copy of or link to all data
you used for the data analytics solution
• web sources that were used to
acquire the data or segments of third-party code to support the application
• other relevant project
deliverables
J. Acknowledge sources, using
in-text citations and references, for content that is quoted, paraphrased, or
summarized.
K. Demonstrate professional
communication in the content and presentation of your submission.
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