College of Doctoral Studies RES-850 Using MaxQ.docx

College of Doctoral Studies
RES-850 Using MaxQDA Assignment Resource
MAXQDA is a software tool designed to assist in the analysis
of qualitative data. It should be noted that MAXQDA does not
create codes or perform analyses independently; the researcher
must create the necessary codes and manipulate the data to gain
insight. However, MAXQDA simplifies the analysis process.
After completing this assignment, you should plan to further
explore MAXQDA to gain familiarity with this software. It will
be used in subsequent courses.
Follow the steps below to complete the assignment, "Using
MAXQDA."
1. Download the MAXQDA software from DC. When prompted,
enter the license code found on the MAXQDA page in DC.
When the download is complete, open MAXQDA.
2. View the "Getting Started Tutorial" in MAXQDA (see
below). The video is approximately 7 minutes in length. This
video also demonstrates the code system. Though the
assignment will not require the importing of documents, this
video offers a good idea of how the software program works. A
more in-depth webinar, "Optional: MAXQDA Webinar," is also
available in the Loud Cloud course materials for this topic.
3. Download the "MAXQDA Getting Started Guide" as shown
below. Review the Guide to gain an understanding of how the
interface works as well as explanation of the standard toolbar

and the key words you will need to understand prior to
reviewing data. Pay close attention to pages 20-25 as they show
how to code and activate documents.
4. In the MAXQDA Welcome dialogue window, click "Open
Examples".

5. Then, click on the file "ENG/Life Satisfaction.mx18", the
first project file listed under the drop-down menu. If prompted,
do not back up the project (click "No.")
6. Once you have opened “Eng/Life Satisfaction.mx18” by
clicking on it, help is available by clicking on the icon in the
top toolbar and then clicking the question mark "Help" icon at
the far right of the page near the top.

7. From the top toolbar in MaxQDA, click on “Home.” Explore
the available views (Document System, Code System, Document
Browser, and Retrieved Segments). Pay close attention to the
different data sources that were included in this sample project:
documents, a focus group, Twitter data, videos, and images.
Views
8. In the Document System view, right Click on "Documents"
(under the tool bar), and activate all documents. The activated
document titles change color. This allows the user to click on a
document, open it in a new browser window, and see all
comments from one person in the document saved under his or
her name. A right click on the focus group transcript permits
opening the actual transcript.

9. Double click on Joanna's name to open Joanna's transcript
and take a screen shot for this assignment.
10. In the Code System view, right click on “Code System”
(under the toolbar), and activate all codes. The code titles
activated will change color. This displays codes, such as
People, Assessments, Interviews Main Topics, Word to story
prompts, Autocodes, and Autocode Twitter Data. These are
preliminary codes the researcher has assigned to his/her data.
11. Under the Codes, you will see subcodes. For example, look
at the code “People.” Underneath the code, you see subcodes of
grandparents, parents, siblings, friends, and partner. These
subcodes represent some further analysis the researcher has
done.
Click on the arrow to the left of the other codes to reveal
subcodes for each.

12. Click on "Interviews Main Topics" code to reveal the
subcodes. Then, double click on the “Career” subcode. Finally,
click on Jon’s name to reveal the paragraph coded for Jon under
the career subcode.
Take a screenshot of Jon’s paragraph-long quote on this topic
for the assignment.
13. At this point, the researcher has developed codes and
subcodes. Review all of the codes and subcodes developed thus
far. Right now, all of the information is at the code or subcode
levels. Researchers need to find a way to collapse these
subcodes into common groups, or categories.
Study each of the subcodes by double clicking on the subcode
and reading the pertinent information. (See bullet point 12
where you opened Jon’s interview for the Career subcode.) Read
through these until you obtain an understanding of what that
particular subcode represents. Once you have an understanding
of the subcodes, think critically to create and define at least
three categories. A category should capture commonalities that
group several subcodes together, or relationships that connect
several subcodes in some way..
Consider the following example when grouping subcodes for
commonality. Under the Assessments code, we see subcodes:
negative, neutral, positive, unclear/ambivalent. Under the Word
to story prompts code, we see subcodes of sadness, happiness,
success and failure. Perhaps one category might be "Emotions."

14. Consider a second example when grouping subcodes for
their relationship. Under the "Interviews Main Topics" code, we
see subcodes of careers, health, home life, recreation,
relationships, and overall satisfaction. Under the "People" code,
we see subcodes of grandparents, parents, siblings, friends, and
partners. Perhaps one category might be “Grandparent’s
Illness.”
Note: Category titles for commonality will typically be shorter
in nature, sometimes even one word, whereas category titles for
relationship will be longer, sometimes multiple words that tie
together codes/subcodes.
15. Create two categories that collapse the subcodes in
Interviews Main Topics and two categories that collapse the
subcodes in People. Write a brief rationale (250-500 words)
describing how you moved from the larger list of subcodes to
each category. Note: Your chosen categories do not have to
encompass all of the subcodes; but, each category must use a
minimum of two subcodes.
In summary, to complete this project you need the following
deliverables:
1. A screenshot of Joanna’s transcript.
2. A screenshot of Jon’s paragraph-long quote.
3. The four categories developed from subcodes.
4. A rationale for the process you used to collapse the subcodes
into groups, or categories.
© 2018. Grand Canyon University. All Rights Reserved.
© 2018. Grand Canyon University. All Rights Reserved.

IT 675 Final Project Guidelines and Rubric
Overview
The final project for this course is a two-part project: an
executive presentation and a technical proposal. The final
project presents a detailed scenario regarding
the merger of two insurance companies. For the project, the
student is positioned as the chief information officer (CIO) and
is asked to lead an initiative to merge
the data infrastructures of both insurance companies into a
single consolidated data warehouse. For the first part of the
project, the student prepares an
executive presentation to outline the project, its importance, and
its scope. For the second part, the student prepares a technical
proposal that outlines in
greater detail how the data from both organizations will be
unified into a data warehouse.
The project is divided into three milestones, which will be
submitted at various points throughout the course to scaffold
learning and ensure quality final
submissions. These milestones will be submitted in Modules
Two, Four, and Six. The Final Project will be submitted in two
parts: Part I in Module Eight and
Part II in Module Nine.
In this assignment you will demonstrate your mastery of the
following course outcomes:
management systems in supporting specific business goals and

decision making
business problems and increase business opportunity
stakeholder needs and business specifications
e constraints and opportunities associated with
integrating data from various systems into a data warehouse
quality by employing appropriate data scrubbing and integration
techniques
Prompts
Scenario
Refer to the following scenario for the background and basis for
your data warehouse design:
Imagine you are the chief information officer (CIO) for Virtual
World Insurance Company, an organization located in San
Diego, California. It provides auto
insurance coverage to more than 100,000 customers across the
United States and currently has 100 employees. Virtual World
Insurance Company has recently
acquired Maxon Insurance Company, located in Ontario,
Canada. Maxon Insurance Company has 10 employees and
provides auto insurance to 10,000 customers
in Canada.
As a result of this merger, the chief executive officer (CEO) has
asked you to look at a data warehouse as a viable solution for
merging both information

technology (IT) infrastructures. After doing research, you
decide to create a data warehouse that will combine the
customer information from both companies
into one centralized location.
Maxon Insurance Company does not have a relational database.
In fact, the company currently stores its data in multiple data
sources. As a result, Maxon
Insurance Company’s data does not have any unique identifiers.
Also, customers with multiple insurance policies have duplicate
records. Each spreadsheet
repeats the customer’s demographic information.
Each insurance company utilizes a distinct customer
relationship management (CRM) system. The CRM systems are
used to keep a record of all customers and
any communications that are sent to customers. The CRM
systems tie into an in-house billing system that is used to bill
for insurance premiums, insurance
deductibles, and any other billable items.
To manage organizational operations, each company uses a
different enterprise resource planning (ERP) system. The ERP
systems are used to manage human
resources (hires, terminations, etc.), payroll, budgeting,
accounting, and fixed assets.
To streamline operations and reduce maintenance costs, all data
systems (ERP, CRM, billing, etc.) will need to be consolidated
into a data warehouse. This will
avoid duplicated information and data redundancy.

Prompt I: Executive Presentation
Prior to creating the technical proposal for the data warehouse,
the CEO would like you to present to the C-level executives the
concepts of a data warehouse.
The purpose of the presentation is to discuss the viability of
creating a data warehouse and providing justification to allocate
resources to complete this project.
Given your research, how viable an option is creating a data
warehouse? What evidence exists to support the decision to
merge the existing IT infrastructures
into a data warehouse? What are the key potential issues and the
key goals that the data warehouse needs to meet? What are some
potential issues you might
face in merging the two infrastructures? Prepare a presentation
that discusses:
I. Concepts of a Data Warehouse: Assess the value of using a
data warehouse. Specifically, discuss the types of information
that a data warehouse should
include and how the information is organized. Why is a data
warehouse the preferred solution? What value would a data
warehouse add to a business?
II. Integration of Data Sources: Discuss in detail the sources of
information that can be integrated from the various operational
areas of the organization.
For example, while some information is housed in Excel
spreadsheets, sales and marketing data may be in a CRM
(customer resource management).
III. Pros and Cons:
a) Cost and Return on Investment: How is the cost of a data

warehouse worth the investment? What type of information can
a data warehouse
provide that would make the cost more acceptable? How will
the organization benefit from a data warehouse? Are there any
negative
consequences of having a data warehouse? Which specific
operational areas will feel the benefits?
b) Required Resources: What are the costs associated with a
data warehouse? Will any additional staff be required to
maintain and support the
data warehouse? Be sure to explain the importance of each
resource you identify.
c) Informational Value: How can the information in a data
warehouse add value to the organization? What specific
business opportunities could be
illuminated and how would the use of a DBMS help solve
business problems?
d) Limitations: What are some functions that a data warehouse
cannot perform? How scalable is a data warehouse? How can
the organization
overcome these obstacles to ensure data quality? Support your
conclusions.
IV. Key Business Considerations: Address some of the
business-related considerations. Some considerations include:
Prior to investing in a specific data
warehouse, what type of hardware and/or software will you
consider? Will you hire a consultant to help with the
implementation process? What is

required prior to moving data to a data warehouse? Will there
be necessary training? Support your conclusions.
V. Closing statement: Summarize the overall presentation with
care. This is your closing statement, the last message to your
audiences and your last chance
to convince them of the value of a data warehouse for solving
their business problems.
Prompt II: Technical Proposal
Having successfully explained the value of designing a
warehouse to facilitate the merger between Virtual World
Insurance Company and Maxon Insurance, you
are now responsible for creating the full-fledged proposal. Your
proposal must include your architecture and a technical plan for
implementation that highlights
potential difficulties. It is important that you communicate in a
manner that can be understood by executives, but can also be
understood by members of your IT
group to plan for future implementation. The challenge will be
balancing audience-appropriate communication with adhering to
the technical nature of your
task. Remember to include all of the necessary aspects of a data
warehouse and to attend to potential issues, both common
aspects and those unique to your
organization.
Your technical proposal must attend to the following critical
elements:
I. Introduction: Provide an introduction that lays the
groundwork for your proposal and tells the audience both what
the point of the proposal is and how it

will benefit the organizations.
II. Data Warehouse Architecture:
a) Architecture Design: Provide a clear visualization of the
architecture, showing the important aspects that will allow for
integration of
organizational information.
b) Architecture Defense: Explain the architecture that you have
designed and the reasoning behind the choices you have made.
What approach did
you take in designing your architecture (for example, did you
follow a top-down or bottom-up approach or did you
incorporate strategies from
multiple approaches)? How will your architecture address
business problems? Be sure to provide support from relevant
sources or examples.
c) Database Management System (DBMS): Provide your
justification and rationale for the DBMS that you select.
Discuss the DBMS tools that you
considered. Why was the DBMS you selected the best choice for
the organization in terms of supporting decision making and
aligning to the
business goals?
III. Implementation Plan:
a) Timeline: Include a reasonable timeline for implementation.
Considerations include: Is there sufficient time between
milestones? What
milestones and key deliverables will be required to complete the

data warehouse from start to finish?
b) Resources: What resources will be required for implementing
the warehouse? Will you use your local IT department or an
external vendor?
What are the approximate costs for this project? Why are the
resources you have identified necessary? Provide examples to
support your claims.
c) Training: Propose a logical training plan for employees. Be
sure to specify the level of training needs for various positions
and explain your
reasoning.
d) Security Policy: Craft a policy for maintaining security that
meets organization needs. Considerations include, but are not
limited to: Who will
have access to the data warehouse? Who will you work with to
determine access rights for users? Will employees have access
to the records
from both companies?
IV. Data Integration and Scrubbing:
a) Data Integrity: How will you combine date fields with
various formats (i.e., MMDDYYYY vs. DDMMYYYY)? What
other data issues will need to be
addressed?
b) Primary Key(s): What will you use as a unique identifier to
combine the records? What primary keys, foreign keys, and
indexes will you need to

create?
c) Customer Data: Once the data is merged into the data
warehouse, how will you be able to differentiate customers from
Virtual World Insurance
Company and customers from Maxon Insurance Company?
d) Duplicate Data: How will you eliminate duplicate records in
the database to ensure data quality?
Milestones
Milestone One: Data Warehouse Pros and Cons Analysis
In Module Two, you will submit your data warehouse pros and
cons analysis. Review the scenario for the final assessment.
Using the scenario, develop a pros
and cons analysis of implementing a data warehouse. Include
the following elements: 1) cost and return on investment (ROI),
2) required resources, 3)
informational value, and 4) limitations. This milestone is graded
with the Milestone One Rubric.
Milestone Two: Implementation Plan
In Module Four, you will submit your implementation plan.
Review the scenario for the final assessment. Using the
scenario, develop this portion of the project
plan. To meet requirements you should include four aspects in
the implementation plan: 1) timeline, 2) resources, 3) training,
and 4) security policy. This
milestone is graded with the Milestone Two Rubric.
Milestone Three: Data Integrity and Scrubbing Portion
In Module Six, you will submit your data integrity and
scrubbing portion of the plan. Review the scenario for the final
assessment. Using the scenario, develop

this portion of the project plan. To meet requirements you will
need to address the four aspects of this subsection of the
proposal, which are as follows: 1) data
integrity, 2) primary key(s), 3) customer data, and 4) duplicate
data. This milestone is graded with the Milestone Three Rubric.
Final Submission: Executive Presentation and Technical
Proposal
In Module Eight, you will submit the first part of your Final
Project, the Executive Presentation, which should outline the
project, its importance, and its scope. It
should be a complete, polished artifact containing all of the
critical elements of the final product. It should reflect the
incorporation of feedback gained
throughout the course. This submission will be graded using
Final Project Rubric I.
In Module Nine, you will submit the second part of your Final
Project, the Technical Proposal, which should outline in greater
detail how the data from both
organizations will be unified into a data warehouse. It should be
a complete, polished artifact containing all of the critical
elements of the final product. It should
reflect the incorporation of feedback gained throughout the
course. This submission will be graded using Final Project
Rubric II.
Deliverables

Milestone Deliverables Module Due Grading
1 Data Warehouse Pros and Cons
Analysis
Two Graded separately; Milestone One Rubric
2 Implementation Plan Four Graded separately; Milestone Two
Rubric
3 Data Integrity and Scrubbing
Portion
Six Graded separately; Milestone Three Rubric
Final Project Submission: Executive
Presentation
Eight Graded separately; Final Project Rubric I
Final Project Submission: Technical
Proposal
Nine Graded separately; Final Project Rubric II
Final Project Rubric I
Guidelines for Submission: Your presentation does not have to
be in the form of a PowerPoint; however, if you use another tool
(such as Prezi), you must prepare
a notes page with your intended speech or you must record
yourself presenting your visual presentation. Remember that an

effective presentation contains main
points and visuals, but the meat of the presentation is in your
verbal communication. The presentation should be
approximately 8–12 slides with notes indicating
intended speech or a recording of yourself giving your
presentation. Remember, this is a professional presentation to
high-level executives, so spelling errors or
unprofessional elements could result in a less-than-favorable
outcome for your proposal.
Critical Elements Exemplary (100%) Proficient (90%) Needs
Improvement (70%) Not Evident (0%) Value
Concepts of a Data
Warehouse
Meets “Proficient” criteria and
assessment of value includes
support from relevant sources
and comparable examples
Provides a logical assessment of
the use and purpose of a data
warehouse with particular
focus on the information
housed in a warehouse and
potential for business solutions
and decision making
Provides an assessment of the
use and purpose of a data
warehouse, but lacks detail on
the information housed in a

warehouse and potential for
business solution and decision
making
Does not provide an overview
of the use and purpose of a
data warehouse
15
Integration of Data
Sources
discussion digs deep into the
specifics of the
operational/functional areas
that are the sources of
information
Discusses the sources of
information that must be
integrated from the various
operational areas of the
organization with accurate
detail and specificity regarding
the place each holds in the
organizational structure
Discusses the sources of
information that must be
organization, but lacks accuracy
or lacks detail and specificity

regarding the place each holds
in the organizational structure
Does not discuss the sources
of information that must be
organization
15
Cost and Return on
Investment
analysis of cost versus value is
centered on the particular
business environment of the
scenario
Provides a detailed and logical
analysis of the cost of
integrating systems versus the
value of a data warehouse
Discusses the cost of
integrating systems versus
value of a data warehouse, but
lacks necessary detail for a
comprehensive analysis
Does not discuss the cost of

10
Required Resources
takes the analysis a step further
by expounding on the
opportunities that may be
presented by attaining such
resources
Accurately analyzes the
particular costs, labor,
equipment, and other
resources that may be required
and explains the importance of
each
Analyzes the particular costs,
labor, equipment, and other
resources that may be required,
but not accurately, or the
importance of each is not
explained accurately
Does not analyze the
resources that may be
required
10

Informational Value
provides specific details and
examples that highlight the
value of data warehouses for
business contexts
business opportunities and
problem-solving capabilities of
the information that can be
housed in a data warehouse
specific to the scenario
Analyzes the business
opportunities and problem-
solving capabilities of the
information that can be housed
in a data warehouse, but not
accurately or specifically to the
scenario
Does not analyze the business
information that can be
15
Data Limitations

support includes relevant
examples and quality sources
Describes common methods for
overcoming possible limitations
of integrating, scaling, and
ensuring data quality with
support
Describes methods for
ensuring data quality, but
description is not
comprehensive or lacks
relevant examples
Does not describe methods for
overcoming possible
limitations of integrating,
scaling, and ensuring data
quality
10
Key Considerations
defense of claims is particularly
well qualified with logic driven
from business context, real-
world examples, and
scholarly/professional sources

Determines key business
considerations from the
scenario and research and
supports claims with examples
and sources that highlight
relevance to increasing
business opportunity
Provides key business
considerations but lacks
supportive sources and
examples that highlight
relevance of considerations to
increasing business opportunity
Does not provide key business
considerations
15
Closing Statements
summary of presentation
highlights the value of a data
warehouse in a manner that
would lend to an acceptance (in
other words, it is persuasive)
Summarizes the overall
presentation with attention to
audience and emphasis on the
Summarizes the overall

presentation, but does not
emphasize the value of a data
warehouse or does not cater to
the audience
Does not summarize the
overall presentation
5
Articulation of
Response
Submission is free of errors
related to citations, grammar,
spelling, syntax, and
organization, and is presented
in a professional and easy-to-
read format
Submission has no major errors
spelling, syntax, or organization
Submission has major errors
that negatively impact
readability and articulation of
main ideas
Submission has critical errors
spelling, syntax, or
organization that prevent

understanding of ideas
5
Earned Total 100%
Rubric Annotations
Term Context for Instructor/Definition
Digs deep into the specifics of the operational/functional
areas
Should dig really deep into the different functions in the
organization, such as accounting,
financial, HR, and so on
Opportunities Fringe benefits/unintended benefits
Provides specific details and examples that highlight the
value of data warehouses for business contexts
Well-detailed discussion regarding “business opportunities and
value”—specifically, this needs
to point to the specific operations in the organization, such as
accounting, finance, marketing,
sales, HR, and so on.
Final Project Rubric II

Guidelines for Submission: Your technical proposal should be
logically organized with all of the key elements of a
professional proposal. There are several types
of proposals (click here for general guidelines for writing
professional proposals), so you must work to cater yours to your
specific content and audience. Your
proposal must include a visual representation of your data
warehouse architecture design, as well as properly cited sources
where appropriate. Submission
lengths will vary.
Introduction Meets “Proficient” criteria and
introduction is particularly well
articulated with specific
examples and logical
identification of key business
factors
Submission includes an
introduction that lays the
groundwork for the proposal
by articulating the business
context and problems at hand
Submission includes an
groundwork for the proposal,
but lacks detail around the
business context and problems
at hand
Submission does not include an

groundwork for the proposal
5
Data Warehouse
Architecture: Design
is creatively represented or
unique in comparison with
other designs
Warehouse design is organized
and clear, and comprehensively
indicates aspects of the
organizational information that
will be integrated
Warehouse design is not clear,
is not organized, or does not
comprehensively indicate all
necessary aspects of the
organizational information that
will be integrated
Does not include a warehouse
design
11.25
Data Warehouse
Architecture:
Architecture Defense

supports defense with real-
world examples and scholarly
sources
Logically defends architecture
design choices and approach
with examples and relevant
sources
Provides reasoning behind
architecture design choices and
approach, but does not defend
with examples and relevant
sources or defense overlooks
relevant factors
Does not provide reasoning
behind architecture design
choices and approach
11.25
https://alicentreid.wordpress.com/2015/04/28/a-practical-guide-
for-writing-proposals/
Data Warehouse
Architecture:
Database
Management System

(DBMS)
defense includes relevant
examples and sources that
provide particularly strong
support
Defends the selection of DBMS
tools in terms of effectively
meeting organizational needs
with logical arguments and
sources of support
Defends the selection of DBMS
tools, but not in terms of
organizational needs or
without logical argument or
sources for support
Does not defend the selection
of DBMS tools
22.5
Implementation Plan:
Timeline
timeline detail is focused
around the key deliverables
required to complete the
warehouse or is exceptionally
well defined in terms of

milestone needs
Crafts a reasonable timeline for
implementation
Crafts a timeline, but the
timeline is not reasonable
Does not craft a timeline 5.62
Resources
specific examples pertain to
the individual organization
Identification of necessary
resources is defended with
specific examples and relevant
explanations
Identification of necessary
resources is defended, but
lacks detail or explanations and
examples are not relevant
Does not defend identification
of necessary resources
5.62
Training

training plan is catered to both
organizations or is
exceptionally well planned
Proposes a logical training plan
for implementation that
includes the reasoning behind
the level of training needs for
various positions
Proposes a training plan, but
lacks detail around level of
training needed or plan is not
entirely logical for
implementation
Does not propose a training
plan
5.62
Security Policy
policy meets organizational
needs to the point of being
ready for implementation
Submission includes a security
policy that considers
permission levels and access
rights, and meets

organizational needs
Submission includes a security
policy that considers
rights, but the policy does not
meet organizational needs
Submission does not include a
security policy that considers
5.62
Data Integration and
Scrubbing: Data
Integrity
methods described are the
best methods for ensuring data
integrity for the given scenario
and specific issue
Articulates the correct methods
for combining data fields with
various formats to ensure data
is not lost or compromised
Articulates methods for
combining data fields with
various formats, but methods
are not correct for ensuring
data is not lost or compromised

Does not articulate methods
for combining data fields with
various formats
5.63
Scrubbing: Primary
Keys
identified keys and indexes are
the most appropriate for each
of their designated purposes
within the data warehouse
Articulates appropriate primary
keys, foreign keys, and indexes
for creation that will ensure a
clear and accurate warehouse
Articulates primary keys,
foreign keys, and indexes
necessary, but not all will
ensure a clear and accurate
warehouse
Does not articulate primary
keys, foreign keys, and indexes
necessary
5.63

Scrubbing: Customer
Data
articulated methods are the
most appropriate given the
accompanying explanation,
accompanying scenario, and
integration issues that have
been identified in the proposal
Articulates plausible methods
for differentiating customer
data from each company after
data is merged
Articulates methods for
differentiating customer data
from each company after data
is merged, but not all methods
are plausible, or necessary
detail is left out of explanation
Does not articulate methods
for differentiating between
customer data from each
company after data is merged
5.63

Scrubbing: Duplicate
Data
identified strategies are the
most appropriate given the
accompanying explanation,
accompanying scenario, and
integration issues that have
been identified in the proposal
Articulates valid, plausible
strategies for eliminating
duplicate records and ensuring
data quality and accuracy
Articulates strategies for
eliminating duplicate records
and ensuring data quality and
accuracy, but not all strategies
are valid or plausible
Does not articulate strategies
for eliminating duplicate
records to ensure data quality
and accuracy
5.63
Articulation of
Response

read format
main ideas
that prevent understanding of
ideas
5
Earned Total 100%
Rubric Annotations
Term Context for Instructor/Definition
Defends architecture design
choices and approach

Additional context for consideration (in terms of the approach
aspect of this critical element):
Will this be a comparison of the different approaches? Top
down vs. bottom up? Student chooses one and follows it
through?
Reasonable The timeline points of interest are spaced in a
realistic manner without unnecessary lapse time.
Ready for implementation Includes sufficient detail and covers
necessary considerations for immediate implementation in the
organizations listed.
There are no obvious barriers to immediate implementation of
the policy for security (once the warehouse is
constructed, of course).
Best methods Most appropriate for each given integration
problem. For example, the proposed method for solving the
issue of
MMDDYYYY versus DDMMYYYY is not only a method that
will work, but also is the most straightforward and appropriate
method for that specific issue.
Designated purposes At minimum, each primary key (for
example) accurately and succinctly acts as the unique identifier
for whatever it is
representing.
Most appropriate Not only are all of the methods realistic and
possible for differentiating customer data, but the methods
discussed fit
within the scenario provided, are fully explained and defended

as the most appropriate given any restraints or issues
that have been identified, or are the most appropriate given the
expertise of the subject matter expert who is evaluating
the submission (the instructor).
IT 675 Milestone One Rubric: Data Warehouse Pros and Cons
Analysis Rubric
The final project for this course is a two-part project: an
executive presentation and a technical proposal. The final
project presents a detailed scenario regarding
the merger of two insurance companies. For the project, the
student is positioned as the chief information officer (CIO) and
is asked to lead an initiative to merge
the data infrastructures of both insurance companies into a
single consolidated data warehouse. For this milestone (due in
Module Two), you will submit your
data warehouse pros and cons analysis. Review the scenario for
the final assessment. Using the scenario, develop a pros and
cons analysis of implementing a
data warehouse. Include the following elements: 1) cost and
return on investment (ROI), 2) required resources, 3)
informational value, and 4) limitations.
The following critical elements will be addressed in this
submission:
Pros and Cons:

a) Cost and Return on Investment: How is the cost of a data
warehouse worth the investment? What type of information can
a data warehouse provide
that would make the cost more acceptable? How will the
organization benefit from a data warehouse? Are there any
negative consequences of having a
data warehouse? Which specific operational areas will feel the
benefits?
b) Required Resources: What are the costs associated with a
data warehouse? Will any additional staff be required to
maintain and support the data
warehouse? Be sure to explain the importance of each resource
you identify.
c) Informational Value: How can the information in a data
warehouse add value to the organization? What specific
business opportunities could be
illuminated and how would the use of a DBMS help solve
business problems?
d) Limitations: What are some functions that a data warehouse
cannot perform? How scalable is a data warehouse? How can
the organization overcome
these obstacles to ensure data quality? Support your
conclusions.
Requirements of Submission: Written components of projects
must follow these formatting guidelines when applicable:
double spacing, 12-point Times New Roman
font, one-inch margins, and discipline-appropriate citations.

Cost and Return on
Investment
analysis of cost versus value is
centered on the particular
business environment of the
scenario
Provides a detailed and logical
analysis of the cost of
Discusses the cost of integrating
systems versus value of a data
warehouse, but lacks necessary
detail for a comprehensive
analysis
Does not discuss the cost of
20
Required Resources Meets “Proficient” criteria and
takes the analysis a step further
by expounding on the
opportunities that may be
presented by attaining such
resources

resources that may be required
and explains the importance of
each
Analyzes the particular costs,
labor, equipment, and other
resources that may be required,
but not accurately, or the
importance of each is not
explained accurately
Does not analyze the particular
costs, labor, equipment, and
other resources that may be
required
20
Informational Value Meets “Proficient” criteria and
provides specific details and
examples that highlight the
value of data warehouses for
business contexts
business opportunities and
problem-solving capabilities of
the information that can be
specific to the scenario
Analyzes the business

in a data warehouse, but not
accurately or specifically to the
scenario
Does not analyze the business
in a data warehouse
20
Data Limitations Meets “Proficient” criteria and
support includes relevant
examples and quality sources
Describes common methods for
ensuring data quality with
support
Describes methods for
ensuring data quality, but is not
comprehensive or lacks
relevant examples
Does not describe methods for
ensuring data quality

20
Articulation of
Response
read format
main ideas
that prevent understanding of
ideas
20
Earned Total 100%

College of Doctoral Studies RES-850 Using MaxQ.docx

College of Doctoral Studies RES-850 Using MaxQ.docx

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