IT 675 Milestone Three Rubric: Data Integrity and Scrubbing Portion
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it_675_milestone_three_rubric.rtf
IT 675 Milestone Three Rubric: Data Integrity and Scrubbing Portion
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 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.
The following critical elements will be addressed in this submission:
Data Integration and Scrubbing:
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?
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?
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?
Duplicate Data: How will you eliminate duplicate records in the database to ensure data quality?
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.
Instructor Feedback: This activity uses an integrated rubric in Blackboard. Students can view instructor feedback in the Grade Center. For more information, review these instructions.
Critical Elements
Exemplary (100%)
Proficient (90%)
Needs Improvement (75%)
Not Evident (0%)
Value
Data Integration and
Meets “Proficient” criteria and
Articulates the correct methods
Articulates methods for
Does not articulate methods for
20
Scrubbing: Data
methods described are the best
for combining data fields with
combining data fields with
combining data fields with
Integrity
methods for ensuring data
various formats to ensure data
various formats, but methods
various formats
integrity for the given scenario
is not lost or compromised
are not correct for ensuring
and specific issue
data is not lost or compromised
Data Integration and
Meets “Proficient” criteria and
Articulates appropriate primary
Articulates primary keys, foreign
Does not articulate primary
20
Scrubbing: Primary
identified keys and indexes are
keys, foreign keys, and indexes
keys, and indexes necessary, but
keys, foreign keys, and indexes
Keys
the most appropriate for each
for creation that will ensure a
not all will ensure a clear and
necessary
of their designated purposes
clear and accurate warehouse
accurate warehouse
within the data warehouse
Data Integration and
Meets “Proficient” criteria and
Articulates plausible methods
Articulates methods for
Does not articulate methods for
20
Scrubbing: Customer
articulated methods are the
for differentiating customer
differentiating customer data
differentiating between
Data
most appropriate given the
data from each company after
from each company after data is
customer data from each
accompanying explanation,
data is merged
merged, but not all methods are
company after data is merged
accompanying scenario, and
plausible, or necessary detail is
integration issues that have
left out of explanation
been identified in the proposal
Data Integration and
Meets “Proficient” criteria and
Articulates valid, plausible
Articulates strategies for
Does not articulate strategies
20
Scrubbing: Duplicate
identified strategies are the
strategies for eliminating
eliminating duplicate records
for eliminating duplicate records
Data
most appropriate given the
duplicate records and ensuring
and ensuring data quality and
to ensure data quality and
accompanying explanation,
data quality and accuracy
accuracy, but not all strategies
accuracy
accompanying scenario, and
are valid or plausible
integration issues that have
been identified in the proposal
Articulation of
Submission is free of errors
Submission has no major errors
Submission has major errors
Submission has critical errors
20
Response
related to citations, grammar,
related to citations, grammar,
related to citations, grammar,
related to citations, grammar,
spelling, syntax, and
spelling, syntax, or organization
spelling, syntax, or organization
spelling, syntax, or organization
organization, and is presented
that negatively impact
that prevent understanding of
in a professional and easy-to-
readability and articulation of
ideas
read format
main ideas
Earned Total
100%
